Text Generation
Transformers
Safetensors
English
phi3
conversational
custom_code
text-generation-inference
Instructions to use numind/NuExtract with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use numind/NuExtract with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="numind/NuExtract", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("numind/NuExtract", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("numind/NuExtract", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use numind/NuExtract with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "numind/NuExtract" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "numind/NuExtract", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/numind/NuExtract
- SGLang
How to use numind/NuExtract with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "numind/NuExtract" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "numind/NuExtract", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "numind/NuExtract" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "numind/NuExtract", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use numind/NuExtract with Docker Model Runner:
docker model run hf.co/numind/NuExtract
Using tiny...not able to extract correctly...
#19 opened 8 months ago
by
padysrini
how to improve accuracy and pdf size limit
1
#18 opened 9 months ago
by
sanamulani1108
When I am running the pipleline, I am getting this error
1
#16 opened 10 months ago
by
Adarshtiwari144
<|input|> Were these used as special tokens during training <|output|>
2
#15 opened over 1 year ago
by
aschroeder91
Bug in Usage Example Code
#14 opened over 1 year ago
by
gregrrr
Benchmark Dataset and evaluation metric
#13 opened over 1 year ago
by
colbylvickerson
How to process more than 1 input at a time?
#10 opened almost 2 years ago
by
calistatan03
How to Prevent the Model from Extracting Incorrect Data?
#9 opened almost 2 years ago
by
Nafiy
Training questions
1
#7 opened almost 2 years ago
by
deoxykev
Schema format
1
#5 opened almost 2 years ago
by
baconnier
In need of muchmuch larger context
1
#4 opened almost 2 years ago
by
matbee