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internlm
/
internlm-20b

Text Generation
Transformers
PyTorch
internlm
feature-extraction
custom_code
Model card Files Files and versions
xet
Community
7

Instructions to use internlm/internlm-20b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use internlm/internlm-20b with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="internlm/internlm-20b", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("internlm/internlm-20b", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use internlm/internlm-20b with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "internlm/internlm-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-20b",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/internlm/internlm-20b
  • SGLang

    How to use internlm/internlm-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-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-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-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-20b",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use internlm/internlm-20b with Docker Model Runner:

    docker model run hf.co/internlm/internlm-20b
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Adding `safetensors` variant of this model

#7 opened over 1 year ago by
SFconvertbot

Adding Evaluation Results

#5 opened over 2 years ago by
leaderboard-pr-bot

用transformers的流式推理(TextIteratorStreamer),出现最后一个token,重复前一个字的问题。

#3 opened over 2 years ago by
Mingtong123

Move to in-library checkpoint

1
#2 opened over 2 years ago by
Rocketknight1

Pretraining details?

🤗 2
#1 opened over 2 years ago by
devingulliver
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