Instructions to use internlm/internlm-chat-20b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use internlm/internlm-chat-20b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="internlm/internlm-chat-20b", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("internlm/internlm-chat-20b", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use internlm/internlm-chat-20b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "internlm/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": "internlm/internlm-chat-20b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/internlm/internlm-chat-20b
- SGLang
How to use internlm/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 "internlm/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": "internlm/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 "internlm/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": "internlm/internlm-chat-20b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use internlm/internlm-chat-20b with Docker Model Runner:
docker model run hf.co/internlm/internlm-chat-20b
Commit History
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update copyright (#16)
Verified signature- update copyright (bca840b38dd2147a45e5d27ec2adf7b9251c3a18) Co-authored-by: Shuhao Xing <x54-729@users.noreply.huggingface.co>ce6e015
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remove unnecessary attention_drop
x54-7298ce92fe
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fix import error
x54-7298c34d3f -
update config
x54-729b832675 -
support flash attn 2
x54-7292f2f1b1
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Update configuration_internlm.py
Verified signature497af06
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Update modeling_internlm.py
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v1.0.3 (#14)
- v1.0.3 (d09e9ea0a1c4e9113327bf844a847fbf9fb22a0c)c823b34
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Update config.json
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Add stream_chat example
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Add torch_dtype to README example
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Support dynamic ntk rope
dec6d2e -
Support dynamic ntk rope
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Support dynamic ntk rope
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fix pad_token_id
c67e80e
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Fix InternLMTokenizer
5f04618
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Small change to chat prompt
bb65b6c
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Add github link
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Update README.md
6f15759 -
Update README.md
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Update README.md
d85414b -
update max_position_embeddings
98802ac -
Create README.md
908decb
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update max_position_embedding
aa83c41
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Upload internlm-20b-chat
7994622 -
initial commit
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