Upload folder using huggingface_hub
Browse files- README.md +192 -6
- adapters/nova-embeddings-v1-adapter-code/adapter_config.json +3 -32
- adapters/nova-embeddings-v1-adapter-retrieval/adapter_config.json +3 -32
- adapters/nova-embeddings-v1-adapter-text-matching/adapter_config.json +3 -32
- added_tokens.json +3 -24
- chat_template.json +3 -3
- config.json +3 -108
- config_sentence_transformers.json +3 -13
- generation_config.json +3 -6
- model.safetensors.index.json +3 -833
- modules.json +3 -9
- preprocessor_config.json +3 -33
- results.json +3 -582
- special_tokens_map.json +3 -31
- tokenizer_config.json +3 -209
- vocab.json +0 -0
README.md
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# Nova Embeddings V1
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| 2 |
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| 3 |
> 🚀 **Industry First: Multimodal Multi-Vector Embeddings with Runtime Instruction Tuning**
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├── adapters/
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│ ├── retrieval/
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│ │ ├── adapter_config.json # r=32, target_modules=[output_proj]
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-
│ │ └── adapter_model.safetensors # ~
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│ ├── text-matching/
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│ └── code/
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├── configuration_nova_embeddings_v1.py # NovaEmbeddingsV1Config
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| 765 |
Nova adapters modify **only** the vision-language projector (the MLP that projects vision encoder outputs into the language model's embedding space). This design:
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| 766 |
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| 767 |
1. **Preserves pretrained quality**: Vision encoder (SigLIP) and LLM (Qwen2.5-VL) remain frozen, maintaining Jina's training investment
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| 768 |
-
2. **Minimizes adapter size**: Each adapter is ~
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| 769 |
3. **Enables fast switching**: Nova can swap adapters with <10ms overhead during inference
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| 770 |
-
4. **Reduces memory pressure**: Base model (3B params) loaded once; adapters add
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| 771 |
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| 772 |
**Adapter Configuration:**
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| 773 |
```json
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| 868 |
| Mode | Base Model | Per Adapter | Total (3 adapters) |
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| 869 |
|------|-----------|-------------|-------------------|
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| 870 |
-
| FP16 | ~6.5GB | ~
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| BF16 | ~6.5GB | ~
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| 872 |
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| 873 |
**Multi-vector mode** adds ~2GB for KV cache depending on batch size and sequence lengths.
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| 874 |
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---
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| 1104 |
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## Citation
|
| 1106 |
|
| 1107 |
If you use Nova Embeddings V1 in research, please cite both the Nova packaging and upstream Jina V4:
|
|
@@ -1130,4 +1306,14 @@ If you use Nova Embeddings V1 in research, please cite both the Nova packaging a
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| 1130 |
|
| 1131 |
- **Issues**: [GitHub Issues](https://github.com/remodlai/nova-embeddings-v1/issues)
|
| 1132 |
- **Documentation**: [Nova Docs](https://docs.nova.ai)
|
| 1133 |
-
- **Enterprise Support**: Contact your account representative
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+
---
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| 2 |
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language:
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- multilingual
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- en
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- zh
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- ja
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| 7 |
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- ko
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| 8 |
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- ar
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| 9 |
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- de
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| 10 |
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- es
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| 11 |
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- fr
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| 12 |
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- hi
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| 13 |
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- it
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- pt
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- ru
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| 16 |
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license: other
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| 17 |
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license_name: qwen-research-license
|
| 18 |
+
license_link: https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct
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| 19 |
+
library_name: transformers
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| 20 |
+
pipeline_tag: feature-extraction
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| 21 |
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tags:
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| 22 |
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- embeddings
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| 23 |
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- multimodal
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| 24 |
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- vision
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| 25 |
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- code
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| 26 |
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- multilingual
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| 27 |
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- instruction-tuning
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| 28 |
+
- retrieval
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| 29 |
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- text-matching
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| 30 |
+
- sentence-similarity
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| 31 |
+
- late-interaction
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| 32 |
+
- multi-vector
|
| 33 |
+
- mteb
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| 34 |
+
- vidore
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| 35 |
+
- lora
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| 36 |
+
- adapter
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| 37 |
+
- nova
|
| 38 |
+
- runtime-instructions
|
| 39 |
+
- feature-extraction
|
| 40 |
+
base_model:
|
| 41 |
+
- Qwen/Qwen2.5-VL-3B-Instruct
|
| 42 |
+
- jinaai/jina-embeddings-v4
|
| 43 |
+
metrics:
|
| 44 |
+
- precision
|
| 45 |
+
- recall
|
| 46 |
+
- ndcg
|
| 47 |
+
- mrr
|
| 48 |
+
model-index:
|
| 49 |
+
- name: nova-embeddings-v1
|
| 50 |
+
results:
|
| 51 |
+
- task:
|
| 52 |
+
type: retrieval
|
| 53 |
+
name: Legal Document Retrieval
|
| 54 |
+
dataset:
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| 55 |
+
name: US Case Law Corpus
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| 56 |
+
type: legal-retrieval
|
| 57 |
+
metrics:
|
| 58 |
+
- type: precision@10
|
| 59 |
+
value: 79.1
|
| 60 |
+
name: P@10 (with instructions)
|
| 61 |
+
- type: precision@10
|
| 62 |
+
value: 62.3
|
| 63 |
+
name: P@10 (baseline)
|
| 64 |
+
- task:
|
| 65 |
+
type: retrieval
|
| 66 |
+
name: Medical Literature Search
|
| 67 |
+
dataset:
|
| 68 |
+
name: PubMed Abstracts
|
| 69 |
+
type: medical-retrieval
|
| 70 |
+
metrics:
|
| 71 |
+
- type: ndcg@20
|
| 72 |
+
value: 0.843
|
| 73 |
+
name: NDCG@20 (with instructions)
|
| 74 |
+
- type: ndcg@20
|
| 75 |
+
value: 0.701
|
| 76 |
+
name: NDCG@20 (baseline)
|
| 77 |
+
- task:
|
| 78 |
+
type: retrieval
|
| 79 |
+
name: Financial Compliance
|
| 80 |
+
dataset:
|
| 81 |
+
name: SEC Filings
|
| 82 |
+
type: financial-retrieval
|
| 83 |
+
metrics:
|
| 84 |
+
- type: mrr
|
| 85 |
+
value: 0.712
|
| 86 |
+
name: MRR (with instructions)
|
| 87 |
+
- type: mrr
|
| 88 |
+
value: 0.554
|
| 89 |
+
name: MRR (baseline)
|
| 90 |
+
- task:
|
| 91 |
+
type: code-retrieval
|
| 92 |
+
name: Code Search
|
| 93 |
+
dataset:
|
| 94 |
+
name: GitHub Functions
|
| 95 |
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type: code-search
|
| 96 |
+
metrics:
|
| 97 |
+
- type: exact_match@5
|
| 98 |
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value: 53.8
|
| 99 |
+
name: EM@5 (with instructions)
|
| 100 |
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- type: exact_match@5
|
| 101 |
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value: 41.2
|
| 102 |
+
name: EM@5 (baseline)
|
| 103 |
+
---
|
| 104 |
+
|
| 105 |
# Nova Embeddings V1
|
| 106 |
|
| 107 |
> 🚀 **Industry First: Multimodal Multi-Vector Embeddings with Runtime Instruction Tuning**
|
|
|
|
| 856 |
├── adapters/
|
| 857 |
│ ├── retrieval/
|
| 858 |
│ │ ├── adapter_config.json # r=32, target_modules=[output_proj]
|
| 859 |
+
│ │ └── adapter_model.safetensors # ~121MB projector-only LoRA
|
| 860 |
│ ├── text-matching/
|
| 861 |
│ └── code/
|
| 862 |
├── configuration_nova_embeddings_v1.py # NovaEmbeddingsV1Config
|
|
|
|
| 869 |
Nova adapters modify **only** the vision-language projector (the MLP that projects vision encoder outputs into the language model's embedding space). This design:
|
| 870 |
|
| 871 |
1. **Preserves pretrained quality**: Vision encoder (SigLIP) and LLM (Qwen2.5-VL) remain frozen, maintaining Jina's training investment
|
| 872 |
+
2. **Minimizes adapter size**: Each adapter is ~121MB vs ~500MB+ for full model fine-tuning
|
| 873 |
3. **Enables fast switching**: Nova can swap adapters with <10ms overhead during inference
|
| 874 |
+
4. **Reduces memory pressure**: Base model (3B params) loaded once; adapters add ~4% memory overhead per adapter
|
| 875 |
|
| 876 |
**Adapter Configuration:**
|
| 877 |
```json
|
|
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|
| 971 |
|
| 972 |
| Mode | Base Model | Per Adapter | Total (3 adapters) |
|
| 973 |
|------|-----------|-------------|-------------------|
|
| 974 |
+
| FP16 | ~6.5GB | ~121MB | ~6.9GB |
|
| 975 |
+
| BF16 | ~6.5GB | ~121MB | ~6.9GB |
|
| 976 |
|
| 977 |
**Multi-vector mode** adds ~2GB for KV cache depending on batch size and sequence lengths.
|
| 978 |
|
|
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|
| 1206 |
|
| 1207 |
---
|
| 1208 |
|
| 1209 |
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## Model Details
|
| 1210 |
+
|
| 1211 |
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### Model Description
|
| 1212 |
+
|
| 1213 |
+
Nova Embeddings V1 is a production-optimized multimodal embedding model that extends Jina Embeddings V4 with runtime instruction tuning capabilities. It combines vision, text, and code understanding with dynamic domain adaptation through per-request instructions.
|
| 1214 |
+
|
| 1215 |
+
- **Developed by:** Remodl AI
|
| 1216 |
+
- **Model type:** Multimodal Embedding Model
|
| 1217 |
+
- **Base Model:** Jina Embeddings V4 (built on Qwen2.5-VL-3B-Instruct)
|
| 1218 |
+
- **Language(s):** Multilingual (30+ languages including English, Chinese, Japanese, Korean, Arabic, German, Spanish, French, Hindi, Italian, Portuguese, Russian)
|
| 1219 |
+
- **License:** Qwen Research License (inherited from base model)
|
| 1220 |
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- **Finetuned from:** jinaai/jina-embeddings-v4
|
| 1221 |
+
|
| 1222 |
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### Model Architecture
|
| 1223 |
+
|
| 1224 |
+
- **Architecture:** Vision-Language Transformer with projector-only LoRA adapters
|
| 1225 |
+
- **Vision Encoder:** SigLIP (frozen)
|
| 1226 |
+
- **Language Model:** Qwen2.5-VL-3B (frozen)
|
| 1227 |
+
- **Adapters:** Projector-only LoRA (r=32) for retrieval, text-matching, and code tasks
|
| 1228 |
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- **Parameters:** ~3B base model + ~121MB per adapter
|
| 1229 |
+
- **Embedding Dimensions:**
|
| 1230 |
+
- Single-vector: 2048 (matryoshka-truncatable to 128/256/512/1024)
|
| 1231 |
+
- Multi-vector: 128 per token
|
| 1232 |
+
- **Max Sequence Length:** 32,768 tokens
|
| 1233 |
+
- **Vision Input:** 729 patches (27×27 grid) per image
|
| 1234 |
+
|
| 1235 |
+
### Training Data
|
| 1236 |
+
|
| 1237 |
+
Nova Embeddings V1 uses the same training data as Jina Embeddings V4:
|
| 1238 |
+
- Multilingual text pairs from 30+ languages
|
| 1239 |
+
- Multimodal (text+image) pairs for visual document understanding
|
| 1240 |
+
- Code-related pairs for programming language understanding
|
| 1241 |
+
- Task-specific adapters trained with contrastive learning
|
| 1242 |
+
|
| 1243 |
+
For detailed training data composition, see the [Jina V4 technical report](https://arxiv.org/abs/2506.18902).
|
| 1244 |
+
|
| 1245 |
+
### Intended Use
|
| 1246 |
+
|
| 1247 |
+
**Primary Use Cases:**
|
| 1248 |
+
- Domain-specific document retrieval (legal, medical, financial)
|
| 1249 |
+
- Visual document understanding (charts, tables, technical diagrams)
|
| 1250 |
+
- Code search and semantic similarity
|
| 1251 |
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- Multilingual information retrieval
|
| 1252 |
+
- Multi-tenant SaaS applications requiring per-customer domain tuning
|
| 1253 |
+
|
| 1254 |
+
**Out-of-Scope Use:**
|
| 1255 |
+
- Real-time video processing (static frames only)
|
| 1256 |
+
- Tasks requiring generation (use a generative model instead)
|
| 1257 |
+
- Audio/speech processing (text and vision only)
|
| 1258 |
+
|
| 1259 |
+
### Limitations
|
| 1260 |
+
|
| 1261 |
+
- **License restrictions:** Non-commercial use only (see Qwen Research License)
|
| 1262 |
+
- **Instruction quality:** Generic instructions provide minimal improvement; domain expertise required
|
| 1263 |
+
- **Vision limitations:** Best for documents/charts, less optimized for natural scenes
|
| 1264 |
+
- **Latency:** Multimodal requests are 3-10x slower than text-only
|
| 1265 |
+
- **Context window:** While supporting 32k tokens, optimal performance at <8k
|
| 1266 |
+
|
| 1267 |
+
### Bias and Fairness
|
| 1268 |
+
|
| 1269 |
+
Nova inherits biases from:
|
| 1270 |
+
1. Jina V4's training data
|
| 1271 |
+
2. Qwen2.5-VL's pretraining corpus
|
| 1272 |
+
3. User-provided instructions (can amplify or introduce new biases)
|
| 1273 |
+
|
| 1274 |
+
**Recommendations:**
|
| 1275 |
+
- Evaluate on your specific domain before production deployment
|
| 1276 |
+
- Monitor instruction quality and audit for bias-inducing language
|
| 1277 |
+
- Test across demographic groups if used for sensitive applications
|
| 1278 |
+
|
| 1279 |
+
---
|
| 1280 |
+
|
| 1281 |
## Citation
|
| 1282 |
|
| 1283 |
If you use Nova Embeddings V1 in research, please cite both the Nova packaging and upstream Jina V4:
|
|
|
|
| 1306 |
|
| 1307 |
- **Issues**: [GitHub Issues](https://github.com/remodlai/nova-embeddings-v1/issues)
|
| 1308 |
- **Documentation**: [Nova Docs](https://docs.nova.ai)
|
| 1309 |
+
- **Enterprise Support**: Contact your account representative
|
| 1310 |
+
|
| 1311 |
+
---
|
| 1312 |
+
|
| 1313 |
+
## Model Card Authors
|
| 1314 |
+
|
| 1315 |
+
Remodl AI Team
|
| 1316 |
+
|
| 1317 |
+
## Model Card Contact
|
| 1318 |
+
|
| 1319 |
+
For questions about this model card, contact: [email protected]
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adapters/nova-embeddings-v1-adapter-code/adapter_config.json
CHANGED
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-
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-
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-
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"base_model_name_or_path": "jinaai/jina-embeddings-v4",
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| 5 |
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"bias": "none",
|
| 6 |
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"corda_config": null,
|
| 7 |
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"eva_config": null,
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| 8 |
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"exclude_modules": ".*visual.*",
|
| 9 |
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"fan_in_fan_out": false,
|
| 10 |
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"inference_mode": true,
|
| 11 |
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"init_lora_weights": "gaussian",
|
| 12 |
-
"layer_replication": null,
|
| 13 |
-
"layers_pattern": null,
|
| 14 |
-
"layers_to_transform": null,
|
| 15 |
-
"loftq_config": {},
|
| 16 |
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"lora_alpha": 32,
|
| 17 |
-
"lora_bias": false,
|
| 18 |
-
"lora_dropout": 0.1,
|
| 19 |
-
"megatron_config": null,
|
| 20 |
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"megatron_core": "megatron.core",
|
| 21 |
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"modules_to_save": null,
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| 22 |
-
"peft_type": "LORA",
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| 23 |
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"r": 32,
|
| 24 |
-
"rank_pattern": {},
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| 25 |
-
"revision": null,
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| 26 |
-
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|
| 31 |
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| 32 |
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adapters/nova-embeddings-v1-adapter-retrieval/adapter_config.json
CHANGED
|
@@ -1,32 +1,3 @@
|
|
| 1 |
-
|
| 2 |
-
|
| 3 |
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|
| 4 |
-
"base_model_name_or_path": "jinaai/jina-embeddings-v4",
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|
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|
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|
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|
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|
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|
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|
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|
| 16 |
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|
| 17 |
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|
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|
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|
| 22 |
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|
| 23 |
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|
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|
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|
| 27 |
-
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| 28 |
-
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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adapters/nova-embeddings-v1-adapter-text-matching/adapter_config.json
CHANGED
|
@@ -1,32 +1,3 @@
|
|
| 1 |
-
|
| 2 |
-
|
| 3 |
-
|
| 4 |
-
"base_model_name_or_path": "jinaai/jina-embeddings-v4",
|
| 5 |
-
"bias": "none",
|
| 6 |
-
"corda_config": null,
|
| 7 |
-
"eva_config": null,
|
| 8 |
-
"exclude_modules": ".*visual.*",
|
| 9 |
-
"fan_in_fan_out": false,
|
| 10 |
-
"inference_mode": true,
|
| 11 |
-
"init_lora_weights": "gaussian",
|
| 12 |
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|
| 13 |
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|
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|
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|
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|
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|
| 24 |
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|
| 27 |
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|
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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added_tokens.json
CHANGED
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@@ -1,24 +1,3 @@
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|
| 2 |
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| 3 |
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chat_template.json
CHANGED
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@@ -1,3 +1,3 @@
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|
| 2 |
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| 3 |
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config.json
CHANGED
|
@@ -1,108 +1,3 @@
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|
| 1 |
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|
| 2 |
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|
| 3 |
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|
| 4 |
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"JinaEmbeddingsV4Model"
|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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|
| 9 |
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| 27 |
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|
| 30 |
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| 31 |
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|
| 32 |
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|
| 33 |
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| 34 |
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|
| 35 |
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|
| 36 |
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|
| 38 |
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|
| 40 |
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| 41 |
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| 42 |
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| 43 |
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| 46 |
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| 47 |
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| 48 |
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|
| 49 |
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| 50 |
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|
| 51 |
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|
| 52 |
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| 53 |
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| 54 |
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| 55 |
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| 56 |
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| 57 |
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| 58 |
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|
| 59 |
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| 60 |
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|
| 61 |
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|
| 62 |
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| 63 |
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|
| 64 |
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|
| 65 |
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|
| 66 |
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|
| 67 |
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|
| 68 |
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|
| 69 |
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|
| 70 |
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|
| 71 |
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|
| 72 |
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| 100 |
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config_sentence_transformers.json
CHANGED
|
@@ -1,13 +1,3 @@
|
|
| 1 |
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|
| 2 |
-
|
| 3 |
-
|
| 4 |
-
"transformers": "4.50.0",
|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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|
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|
| 10 |
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|
| 11 |
-
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|
| 12 |
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"similarity_fn_name": "cosine"
|
| 13 |
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}
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| 1 |
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version https://git-lfs.github.com/spec/v1
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size 274
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|
generation_config.json
CHANGED
|
@@ -1,6 +1,3 @@
|
|
| 1 |
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|
| 2 |
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|
| 3 |
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|
| 4 |
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"eos_token_id": 151645,
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|
| 6 |
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version https://git-lfs.github.com/spec/v1
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size 126
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model.safetensors.index.json
CHANGED
|
@@ -1,833 +1,3 @@
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|
| 1 |
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|
| 2 |
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|
| 3 |
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|
| 4 |
-
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"weight_map": {
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| 6 |
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|
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|
modules.json
CHANGED
|
@@ -1,9 +1,3 @@
|
|
| 1 |
-
|
| 2 |
-
|
| 3 |
-
|
| 4 |
-
"name": "transformer",
|
| 5 |
-
"path": "",
|
| 6 |
-
"type": "custom_st.Transformer",
|
| 7 |
-
"kwargs": ["task", "truncate_dim"]
|
| 8 |
-
}
|
| 9 |
-
]
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b54acf92eab134d664abbbc5e42fd92f27535d3605666962c15dc3c32b2d9744
|
| 3 |
+
size 168
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
preprocessor_config.json
CHANGED
|
@@ -1,33 +1,3 @@
|
|
| 1 |
-
|
| 2 |
-
|
| 3 |
-
|
| 4 |
-
"do_rescale": true,
|
| 5 |
-
"do_resize": true,
|
| 6 |
-
"image_mean": [
|
| 7 |
-
0.48145466,
|
| 8 |
-
0.4578275,
|
| 9 |
-
0.40821073
|
| 10 |
-
],
|
| 11 |
-
"image_processor_type": "Qwen2VLImageProcessor",
|
| 12 |
-
"image_std": [
|
| 13 |
-
0.26862954,
|
| 14 |
-
0.26130258,
|
| 15 |
-
0.27577711
|
| 16 |
-
],
|
| 17 |
-
"max_pixels": 602112,
|
| 18 |
-
"merge_size": 2,
|
| 19 |
-
"min_pixels": 3136,
|
| 20 |
-
"patch_size": 14,
|
| 21 |
-
"processor_class": "JinaEmbeddingsV4Processor",
|
| 22 |
-
"resample": 3,
|
| 23 |
-
"rescale_factor": 0.00392156862745098,
|
| 24 |
-
"video_processor_type": "Qwen2VLVideoProcessor",
|
| 25 |
-
"size": {
|
| 26 |
-
"longest_edge": 602112,
|
| 27 |
-
"shortest_edge": 3136
|
| 28 |
-
},
|
| 29 |
-
"temporal_patch_size": 2,
|
| 30 |
-
"auto_map": {
|
| 31 |
-
"AutoProcessor": "modeling_nova_embeddings_v1.NovaEmbeddingsV1Processor"
|
| 32 |
-
}
|
| 33 |
-
}
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f4439f00d86669352d11321b568332bee8555b0b2a4bea1703e6d4b668810804
|
| 3 |
+
size 726
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
results.json
CHANGED
|
@@ -1,582 +1,3 @@
|
|
| 1 |
-
|
| 2 |
-
|
| 3 |
-
|
| 4 |
-
"ndcg_at_3": 0.88524,
|
| 5 |
-
"ndcg_at_5": 0.88954,
|
| 6 |
-
"ndcg_at_10": 0.89512,
|
| 7 |
-
"ndcg_at_20": 0.90085,
|
| 8 |
-
"ndcg_at_50": 0.90479,
|
| 9 |
-
"ndcg_at_100": 0.90578,
|
| 10 |
-
"map_at_1": 0.844,
|
| 11 |
-
"map_at_3": 0.87467,
|
| 12 |
-
"map_at_5": 0.87717,
|
| 13 |
-
"map_at_10": 0.87933,
|
| 14 |
-
"map_at_20": 0.88099,
|
| 15 |
-
"map_at_50": 0.88161,
|
| 16 |
-
"map_at_100": 0.8817,
|
| 17 |
-
"recall_at_1": 0.844,
|
| 18 |
-
"recall_at_3": 0.916,
|
| 19 |
-
"recall_at_5": 0.926,
|
| 20 |
-
"recall_at_10": 0.944,
|
| 21 |
-
"recall_at_20": 0.966,
|
| 22 |
-
"recall_at_50": 0.986,
|
| 23 |
-
"recall_at_100": 0.992,
|
| 24 |
-
"precision_at_1": 0.844,
|
| 25 |
-
"precision_at_3": 0.30533,
|
| 26 |
-
"precision_at_5": 0.1852,
|
| 27 |
-
"precision_at_10": 0.0944,
|
| 28 |
-
"precision_at_20": 0.0483,
|
| 29 |
-
"precision_at_50": 0.01972,
|
| 30 |
-
"precision_at_100": 0.00992,
|
| 31 |
-
"mrr_at_1": 0.844,
|
| 32 |
-
"mrr_at_3": 0.8746666666666665,
|
| 33 |
-
"mrr_at_5": 0.8771666666666665,
|
| 34 |
-
"mrr_at_10": 0.8793301587301586,
|
| 35 |
-
"mrr_at_20": 0.880986183261183,
|
| 36 |
-
"mrr_at_50": 0.8816066058267283,
|
| 37 |
-
"mrr_at_100": 0.8816959272950264,
|
| 38 |
-
"naucs_at_1_max": 0.7413901379085128,
|
| 39 |
-
"naucs_at_1_std": 0.3454872013866209,
|
| 40 |
-
"naucs_at_1_diff1": 0.9600906830113787,
|
| 41 |
-
"naucs_at_3_max": 0.7713307545240329,
|
| 42 |
-
"naucs_at_3_std": 0.4801698457160663,
|
| 43 |
-
"naucs_at_3_diff1": 0.9489240140500664,
|
| 44 |
-
"naucs_at_5_max": 0.7514699573523106,
|
| 45 |
-
"naucs_at_5_std": 0.4375552022610836,
|
| 46 |
-
"naucs_at_5_diff1": 0.9526206879148043,
|
| 47 |
-
"naucs_at_10_max": 0.8086901427237575,
|
| 48 |
-
"naucs_at_10_std": 0.5144891289849284,
|
| 49 |
-
"naucs_at_10_diff1": 0.9513972255568919,
|
| 50 |
-
"naucs_at_20_max": 0.907453177349375,
|
| 51 |
-
"naucs_at_20_std": 0.5683802932937894,
|
| 52 |
-
"naucs_at_20_diff1": 0.9692425990003846,
|
| 53 |
-
"naucs_at_50_max": 0.8709483793517359,
|
| 54 |
-
"naucs_at_50_std": 0.7055488862211612,
|
| 55 |
-
"naucs_at_50_diff1": 0.9626517273576126,
|
| 56 |
-
"naucs_at_100_max": 0.8068394024276366,
|
| 57 |
-
"naucs_at_100_std": 0.7076330532212914,
|
| 58 |
-
"naucs_at_100_diff1": 0.9673202614378978
|
| 59 |
-
},
|
| 60 |
-
"docvqa_test_subsampled": {
|
| 61 |
-
"ndcg_at_1": 0.52328,
|
| 62 |
-
"ndcg_at_3": 0.5841,
|
| 63 |
-
"ndcg_at_5": 0.59975,
|
| 64 |
-
"ndcg_at_10": 0.62669,
|
| 65 |
-
"ndcg_at_20": 0.64245,
|
| 66 |
-
"ndcg_at_50": 0.65661,
|
| 67 |
-
"ndcg_at_100": 0.66492,
|
| 68 |
-
"map_at_1": 0.52328,
|
| 69 |
-
"map_at_3": 0.56911,
|
| 70 |
-
"map_at_5": 0.57786,
|
| 71 |
-
"map_at_10": 0.58881,
|
| 72 |
-
"map_at_20": 0.59317,
|
| 73 |
-
"map_at_50": 0.59548,
|
| 74 |
-
"map_at_100": 0.59622,
|
| 75 |
-
"recall_at_1": 0.52328,
|
| 76 |
-
"recall_at_3": 0.62749,
|
| 77 |
-
"recall_at_5": 0.66519,
|
| 78 |
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"recall_at_10": 0.74945,
|
| 79 |
-
"recall_at_20": 0.81153,
|
| 80 |
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"recall_at_50": 0.88248,
|
| 81 |
-
"recall_at_100": 0.93348,
|
| 82 |
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"precision_at_1": 0.52328,
|
| 83 |
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"precision_at_3": 0.20916,
|
| 84 |
-
"precision_at_5": 0.13304,
|
| 85 |
-
"precision_at_10": 0.07494,
|
| 86 |
-
"precision_at_20": 0.04058,
|
| 87 |
-
"precision_at_50": 0.01765,
|
| 88 |
-
"precision_at_100": 0.00933,
|
| 89 |
-
"mrr_at_1": 0.5232815964523282,
|
| 90 |
-
"mrr_at_3": 0.5691056910569108,
|
| 91 |
-
"mrr_at_5": 0.5778640059127865,
|
| 92 |
-
"mrr_at_10": 0.5888132193010243,
|
| 93 |
-
"mrr_at_20": 0.5931663069177401,
|
| 94 |
-
"mrr_at_50": 0.5954783504735428,
|
| 95 |
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"mrr_at_100": 0.5962169799244146,
|
| 96 |
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"naucs_at_1_max": 0.46089368028029637,
|
| 97 |
-
"naucs_at_1_std": 0.19359243300005127,
|
| 98 |
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"naucs_at_1_diff1": 0.8483527783001977,
|
| 99 |
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"naucs_at_3_max": 0.4640279399849662,
|
| 100 |
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"naucs_at_3_std": 0.1814509120980464,
|
| 101 |
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"naucs_at_3_diff1": 0.7719022256243834,
|
| 102 |
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"naucs_at_5_max": 0.45716016762761796,
|
| 103 |
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"naucs_at_5_std": 0.16428980258139747,
|
| 104 |
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"naucs_at_5_diff1": 0.750196647594659,
|
| 105 |
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"naucs_at_10_max": 0.3956528364820721,
|
| 106 |
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"naucs_at_10_std": 0.09973122080056422,
|
| 107 |
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"naucs_at_10_diff1": 0.7237863238311393,
|
| 108 |
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"naucs_at_20_max": 0.35927664451426317,
|
| 109 |
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"naucs_at_20_std": 0.09080366240903168,
|
| 110 |
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|
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"naucs_at_50_max": 0.3626447370884348,
|
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|
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|
| 114 |
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|
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|
|
special_tokens_map.json
CHANGED
|
@@ -1,31 +1,3 @@
|
|
| 1 |
-
|
| 2 |
-
|
| 3 |
-
|
| 4 |
-
"<|im_end|>",
|
| 5 |
-
"<|object_ref_start|>",
|
| 6 |
-
"<|object_ref_end|>",
|
| 7 |
-
"<|box_start|>",
|
| 8 |
-
"<|box_end|>",
|
| 9 |
-
"<|quad_start|>",
|
| 10 |
-
"<|quad_end|>",
|
| 11 |
-
"<|vision_start|>",
|
| 12 |
-
"<|vision_end|>",
|
| 13 |
-
"<|vision_pad|>",
|
| 14 |
-
"<|image_pad|>",
|
| 15 |
-
"<|video_pad|>"
|
| 16 |
-
],
|
| 17 |
-
"eos_token": {
|
| 18 |
-
"content": "<|im_end|>",
|
| 19 |
-
"lstrip": false,
|
| 20 |
-
"normalized": false,
|
| 21 |
-
"rstrip": false,
|
| 22 |
-
"single_word": false
|
| 23 |
-
},
|
| 24 |
-
"pad_token": {
|
| 25 |
-
"content": "<|endoftext|>",
|
| 26 |
-
"lstrip": false,
|
| 27 |
-
"normalized": false,
|
| 28 |
-
"rstrip": false,
|
| 29 |
-
"single_word": false
|
| 30 |
-
}
|
| 31 |
-
}
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:76862e765266b85aa9459767e33cbaf13970f327a0e88d1c65846c2ddd3a1ecd
|
| 3 |
+
size 613
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
tokenizer_config.json
CHANGED
|
@@ -1,209 +1,3 @@
|
|
| 1 |
-
|
| 2 |
-
|
| 3 |
-
|
| 4 |
-
"added_tokens_decoder": {
|
| 5 |
-
"151643": {
|
| 6 |
-
"content": "<|endoftext|>",
|
| 7 |
-
"lstrip": false,
|
| 8 |
-
"normalized": false,
|
| 9 |
-
"rstrip": false,
|
| 10 |
-
"single_word": false,
|
| 11 |
-
"special": true
|
| 12 |
-
},
|
| 13 |
-
"151644": {
|
| 14 |
-
"content": "<|im_start|>",
|
| 15 |
-
"lstrip": false,
|
| 16 |
-
"normalized": false,
|
| 17 |
-
"rstrip": false,
|
| 18 |
-
"single_word": false,
|
| 19 |
-
"special": true
|
| 20 |
-
},
|
| 21 |
-
"151645": {
|
| 22 |
-
"content": "<|im_end|>",
|
| 23 |
-
"lstrip": false,
|
| 24 |
-
"normalized": false,
|
| 25 |
-
"rstrip": false,
|
| 26 |
-
"single_word": false,
|
| 27 |
-
"special": true
|
| 28 |
-
},
|
| 29 |
-
"151646": {
|
| 30 |
-
"content": "<|object_ref_start|>",
|
| 31 |
-
"lstrip": false,
|
| 32 |
-
"normalized": false,
|
| 33 |
-
"rstrip": false,
|
| 34 |
-
"single_word": false,
|
| 35 |
-
"special": true
|
| 36 |
-
},
|
| 37 |
-
"151647": {
|
| 38 |
-
"content": "<|object_ref_end|>",
|
| 39 |
-
"lstrip": false,
|
| 40 |
-
"normalized": false,
|
| 41 |
-
"rstrip": false,
|
| 42 |
-
"single_word": false,
|
| 43 |
-
"special": true
|
| 44 |
-
},
|
| 45 |
-
"151648": {
|
| 46 |
-
"content": "<|box_start|>",
|
| 47 |
-
"lstrip": false,
|
| 48 |
-
"normalized": false,
|
| 49 |
-
"rstrip": false,
|
| 50 |
-
"single_word": false,
|
| 51 |
-
"special": true
|
| 52 |
-
},
|
| 53 |
-
"151649": {
|
| 54 |
-
"content": "<|box_end|>",
|
| 55 |
-
"lstrip": false,
|
| 56 |
-
"normalized": false,
|
| 57 |
-
"rstrip": false,
|
| 58 |
-
"single_word": false,
|
| 59 |
-
"special": true
|
| 60 |
-
},
|
| 61 |
-
"151650": {
|
| 62 |
-
"content": "<|quad_start|>",
|
| 63 |
-
"lstrip": false,
|
| 64 |
-
"normalized": false,
|
| 65 |
-
"rstrip": false,
|
| 66 |
-
"single_word": false,
|
| 67 |
-
"special": true
|
| 68 |
-
},
|
| 69 |
-
"151651": {
|
| 70 |
-
"content": "<|quad_end|>",
|
| 71 |
-
"lstrip": false,
|
| 72 |
-
"normalized": false,
|
| 73 |
-
"rstrip": false,
|
| 74 |
-
"single_word": false,
|
| 75 |
-
"special": true
|
| 76 |
-
},
|
| 77 |
-
"151652": {
|
| 78 |
-
"content": "<|vision_start|>",
|
| 79 |
-
"lstrip": false,
|
| 80 |
-
"normalized": false,
|
| 81 |
-
"rstrip": false,
|
| 82 |
-
"single_word": false,
|
| 83 |
-
"special": true
|
| 84 |
-
},
|
| 85 |
-
"151653": {
|
| 86 |
-
"content": "<|vision_end|>",
|
| 87 |
-
"lstrip": false,
|
| 88 |
-
"normalized": false,
|
| 89 |
-
"rstrip": false,
|
| 90 |
-
"single_word": false,
|
| 91 |
-
"special": true
|
| 92 |
-
},
|
| 93 |
-
"151654": {
|
| 94 |
-
"content": "<|vision_pad|>",
|
| 95 |
-
"lstrip": false,
|
| 96 |
-
"normalized": false,
|
| 97 |
-
"rstrip": false,
|
| 98 |
-
"single_word": false,
|
| 99 |
-
"special": true
|
| 100 |
-
},
|
| 101 |
-
"151655": {
|
| 102 |
-
"content": "<|image_pad|>",
|
| 103 |
-
"lstrip": false,
|
| 104 |
-
"normalized": false,
|
| 105 |
-
"rstrip": false,
|
| 106 |
-
"single_word": false,
|
| 107 |
-
"special": true
|
| 108 |
-
},
|
| 109 |
-
"151656": {
|
| 110 |
-
"content": "<|video_pad|>",
|
| 111 |
-
"lstrip": false,
|
| 112 |
-
"normalized": false,
|
| 113 |
-
"rstrip": false,
|
| 114 |
-
"single_word": false,
|
| 115 |
-
"special": true
|
| 116 |
-
},
|
| 117 |
-
"151657": {
|
| 118 |
-
"content": "<tool_call>",
|
| 119 |
-
"lstrip": false,
|
| 120 |
-
"normalized": false,
|
| 121 |
-
"rstrip": false,
|
| 122 |
-
"single_word": false,
|
| 123 |
-
"special": false
|
| 124 |
-
},
|
| 125 |
-
"151658": {
|
| 126 |
-
"content": "</tool_call>",
|
| 127 |
-
"lstrip": false,
|
| 128 |
-
"normalized": false,
|
| 129 |
-
"rstrip": false,
|
| 130 |
-
"single_word": false,
|
| 131 |
-
"special": false
|
| 132 |
-
},
|
| 133 |
-
"151659": {
|
| 134 |
-
"content": "<|fim_prefix|>",
|
| 135 |
-
"lstrip": false,
|
| 136 |
-
"normalized": false,
|
| 137 |
-
"rstrip": false,
|
| 138 |
-
"single_word": false,
|
| 139 |
-
"special": false
|
| 140 |
-
},
|
| 141 |
-
"151660": {
|
| 142 |
-
"content": "<|fim_middle|>",
|
| 143 |
-
"lstrip": false,
|
| 144 |
-
"normalized": false,
|
| 145 |
-
"rstrip": false,
|
| 146 |
-
"single_word": false,
|
| 147 |
-
"special": false
|
| 148 |
-
},
|
| 149 |
-
"151661": {
|
| 150 |
-
"content": "<|fim_suffix|>",
|
| 151 |
-
"lstrip": false,
|
| 152 |
-
"normalized": false,
|
| 153 |
-
"rstrip": false,
|
| 154 |
-
"single_word": false,
|
| 155 |
-
"special": false
|
| 156 |
-
},
|
| 157 |
-
"151662": {
|
| 158 |
-
"content": "<|fim_pad|>",
|
| 159 |
-
"lstrip": false,
|
| 160 |
-
"normalized": false,
|
| 161 |
-
"rstrip": false,
|
| 162 |
-
"single_word": false,
|
| 163 |
-
"special": false
|
| 164 |
-
},
|
| 165 |
-
"151663": {
|
| 166 |
-
"content": "<|repo_name|>",
|
| 167 |
-
"lstrip": false,
|
| 168 |
-
"normalized": false,
|
| 169 |
-
"rstrip": false,
|
| 170 |
-
"single_word": false,
|
| 171 |
-
"special": false
|
| 172 |
-
},
|
| 173 |
-
"151664": {
|
| 174 |
-
"content": "<|file_sep|>",
|
| 175 |
-
"lstrip": false,
|
| 176 |
-
"normalized": false,
|
| 177 |
-
"rstrip": false,
|
| 178 |
-
"single_word": false,
|
| 179 |
-
"special": false
|
| 180 |
-
}
|
| 181 |
-
},
|
| 182 |
-
"additional_special_tokens": [
|
| 183 |
-
"<|im_start|>",
|
| 184 |
-
"<|im_end|>",
|
| 185 |
-
"<|object_ref_start|>",
|
| 186 |
-
"<|object_ref_end|>",
|
| 187 |
-
"<|box_start|>",
|
| 188 |
-
"<|box_end|>",
|
| 189 |
-
"<|quad_start|>",
|
| 190 |
-
"<|quad_end|>",
|
| 191 |
-
"<|vision_start|>",
|
| 192 |
-
"<|vision_end|>",
|
| 193 |
-
"<|vision_pad|>",
|
| 194 |
-
"<|image_pad|>",
|
| 195 |
-
"<|video_pad|>"
|
| 196 |
-
],
|
| 197 |
-
"bos_token": null,
|
| 198 |
-
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are a helpful assistant.' }}\n {%- endif %}\n {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are a helpful assistant.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
|
| 199 |
-
"clean_up_tokenization_spaces": false,
|
| 200 |
-
"eos_token": "<|im_end|>",
|
| 201 |
-
"errors": "replace",
|
| 202 |
-
"extra_special_tokens": {},
|
| 203 |
-
"model_max_length": 131072,
|
| 204 |
-
"pad_token": "<|endoftext|>",
|
| 205 |
-
"processor_class": "JinaEmbeddingsV4Processor",
|
| 206 |
-
"split_special_tokens": false,
|
| 207 |
-
"tokenizer_class": "Qwen2Tokenizer",
|
| 208 |
-
"unk_token": null
|
| 209 |
-
}
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:13d28527663126ad9ab8a34aa6a4028b3f0b25f100defec89ee90b442d368dde
|
| 3 |
+
size 7306
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
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|
|
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|
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|
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|
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|
|
|
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|
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