Text Generation
Transformers
Safetensors
llama
llama-factory
full
Generated from Trainer
text-generation-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("OFA-Sys/MuggleMath_70B")
model = AutoModelForCausalLM.from_pretrained("OFA-Sys/MuggleMath_70B")Quick Links
muggle70b
This model is a fine-tuned version of /cpfs01/shared/public/lichengpeng.lcp/Llama-2-70b-hf on the muggle dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 32
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 3.0
Training results
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu118
- Datasets 2.17.1
- Tokenizers 0.15.2
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="OFA-Sys/MuggleMath_70B")