Instructions to use vansin/internlm-chat-20b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vansin/internlm-chat-20b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="vansin/internlm-chat-20b", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("vansin/internlm-chat-20b", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use vansin/internlm-chat-20b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "vansin/internlm-chat-20b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "vansin/internlm-chat-20b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/vansin/internlm-chat-20b
- SGLang
How to use vansin/internlm-chat-20b 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 "vansin/internlm-chat-20b" \ --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": "vansin/internlm-chat-20b", "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 "vansin/internlm-chat-20b" \ --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": "vansin/internlm-chat-20b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use vansin/internlm-chat-20b with Docker Model Runner:
docker model run hf.co/vansin/internlm-chat-20b
Download pytorch_model-00005-of-00005.bin from vansin/internlm-chat-20b: direct link, hf CLI and curl.
- Browser
- Download file 1.06 GB
-
https://huggingface.co/vansin/internlm-chat-20b/resolve/main/pytorch_model-00005-of-00005.bin
- Command line
-
hf download hf://vansin/internlm-chat-20b/pytorch_model-00005-of-00005.bin
-
curl -L -o pytorch_model-00005-of-00005.bin https://huggingface.co/vansin/internlm-chat-20b/resolve/main/pytorch_model-00005-of-00005.bin
1.06 GB
- Xet hash:
- 1a7a163036d7f888b99df41ca3411f480e52b8187aa2a927fa85b4129dae7de6
- Size of remote file:
- 1.06 GB
- SHA256:
- 263f29c6331d8951fd454d4bbd2991d422bbcfb5b07d4acbb0e75aaf53b1a76c
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