Text Generation
Transformers
Safetensors
English
RefinedWebModel
custom_code
text-generation-inference
4-bit precision
gptq
Instructions to use TheBloke/Falcon-7B-Instruct-GPTQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheBloke/Falcon-7B-Instruct-GPTQ with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TheBloke/Falcon-7B-Instruct-GPTQ", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("TheBloke/Falcon-7B-Instruct-GPTQ", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use TheBloke/Falcon-7B-Instruct-GPTQ with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TheBloke/Falcon-7B-Instruct-GPTQ" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TheBloke/Falcon-7B-Instruct-GPTQ", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/TheBloke/Falcon-7B-Instruct-GPTQ
- SGLang
How to use TheBloke/Falcon-7B-Instruct-GPTQ 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 "TheBloke/Falcon-7B-Instruct-GPTQ" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TheBloke/Falcon-7B-Instruct-GPTQ", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "TheBloke/Falcon-7B-Instruct-GPTQ" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TheBloke/Falcon-7B-Instruct-GPTQ", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use TheBloke/Falcon-7B-Instruct-GPTQ with Docker Model Runner:
docker model run hf.co/TheBloke/Falcon-7B-Instruct-GPTQ
Commit History
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Update for Transformers GPTQ support
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Update README.md
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closed the unclosed quote (#11)
- closed the unclosed quote (47770a711652d8bf2f2b2d5f1ff0241db09e7ab2) Co-authored-by: Mohammed Faheem <thefaheem@users.noreply.huggingface.co>f6ecb3e
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Update config.json (#8)
- Update config.json (bb4f2d10ea2fecd636bfce47a741bf89aa47fe6c) Co-authored-by: Mike Ravkine <mike-ravkine@users.noreply.huggingface.co>02ed56a
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Fix eos_token_id to align with vocabulary of this model (#6)
- Fix eos_token_id to align with vocabulary of this model (214ede753741cba42ba95344e4e18f9ab68dce86) Co-authored-by: Mike Ravkine <mike-ravkine@users.noreply.huggingface.co>c943460
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Initial AutoGPTQ model commit.
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Initial AutoGPTQ model commit.
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Initial AutoGPTQ model commit.
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initial commit
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