Text Generation
Transformers
PyTorch
Safetensors
English
llama
Eval Results (legacy)
text-generation-inference
Instructions to use pankajmathur/Lima_Unchained_70b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pankajmathur/Lima_Unchained_70b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="pankajmathur/Lima_Unchained_70b")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("pankajmathur/Lima_Unchained_70b") model = AutoModelForCausalLM.from_pretrained("pankajmathur/Lima_Unchained_70b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use pankajmathur/Lima_Unchained_70b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "pankajmathur/Lima_Unchained_70b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "pankajmathur/Lima_Unchained_70b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/pankajmathur/Lima_Unchained_70b
- SGLang
How to use pankajmathur/Lima_Unchained_70b 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 "pankajmathur/Lima_Unchained_70b" \ --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": "pankajmathur/Lima_Unchained_70b", "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 "pankajmathur/Lima_Unchained_70b" \ --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": "pankajmathur/Lima_Unchained_70b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use pankajmathur/Lima_Unchained_70b with Docker Model Runner:
docker model run hf.co/pankajmathur/Lima_Unchained_70b
Commit History
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Adding `safetensors` variant of this model (#7)
Verified signature- Adding `safetensors` variant of this model (0ca70c8c45f0504d9dc4cb9f357819fd2a5b40e7) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>8f25fde
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Adding Evaluation Results (#6)
Verified signature- Adding Evaluation Results (ebf4db190fc0d065c69516c65a649de626a79083) Co-authored-by: Open LLM Leaderboard PR Bot <leaderboard-pr-bot@users.noreply.huggingface.co>6b018d5
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Adding Evaluation Results (#4)
- Adding Evaluation Results (3901cf7b32a090f1ce63f197863c3586fd1fa12a) Co-authored-by: Open LLM Leaderboard PR Bot <leaderboard-pr-bot@users.noreply.huggingface.co>e1897be
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