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PursuitOfDataScience
/
Argonne2.5-instruct

Text Generation
Transformers
Safetensors
English
argonne2
causal-lm
transformer
argonne
instruct
pretrained
conversational
Model card Files Files and versions
xet
Community

Instructions to use PursuitOfDataScience/Argonne2.5-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use PursuitOfDataScience/Argonne2.5-instruct with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="PursuitOfDataScience/Argonne2.5-instruct")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("PursuitOfDataScience/Argonne2.5-instruct", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use PursuitOfDataScience/Argonne2.5-instruct with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "PursuitOfDataScience/Argonne2.5-instruct"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "PursuitOfDataScience/Argonne2.5-instruct",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/PursuitOfDataScience/Argonne2.5-instruct
  • SGLang

    How to use PursuitOfDataScience/Argonne2.5-instruct 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 "PursuitOfDataScience/Argonne2.5-instruct" \
        --host 0.0.0.0 \
        --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "PursuitOfDataScience/Argonne2.5-instruct",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    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 "PursuitOfDataScience/Argonne2.5-instruct" \
            --host 0.0.0.0 \
            --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "PursuitOfDataScience/Argonne2.5-instruct",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use PursuitOfDataScience/Argonne2.5-instruct with Docker Model Runner:

    docker model run hf.co/PursuitOfDataScience/Argonne2.5-instruct
Argonne2.5-instruct
2.56 GB
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  • 1 contributor
History: 16 commits
PursuitOfDataScience's picture
PursuitOfDataScience
Restore inference snippet with recommended config
654f235 verified 29 days ago
  • .gitattributes
    396 Bytes
    Restore inference snippet with recommended config 29 days ago
  • README.md
    4.03 kB
    Restore inference snippet with recommended config 29 days ago
  • chat_template.jinja
    4.12 kB
    Publish Argonne 2.5 instruct model about 1 month ago
  • config.json
    839 Bytes
    Reupload Argonne 2.5 instruct as bf16 shards about 1 month ago
  • model-00001-of-00005.safetensors
    544 MB
    xet
    Restore inference snippet with recommended config 29 days ago
  • model-00002-of-00005.safetensors
    501 MB
    xet
    Restore inference snippet with recommended config 29 days ago
  • model-00003-of-00005.safetensors
    501 MB
    xet
    Restore inference snippet with recommended config 29 days ago
  • model-00004-of-00005.safetensors
    501 MB
    xet
    Restore inference snippet with recommended config 29 days ago
  • model-00005-of-00005.safetensors
    501 MB
    xet
    Restore inference snippet with recommended config 29 days ago
  • model.py
    23.8 kB
    Update Argonne 2.5-instruct README with recommended config 29 days ago
  • model.safetensors.index.json
    18.3 kB
    Restore inference snippet with recommended config 29 days ago
  • tokenizer.json
    11.4 MB
    xet
    Publish Argonne 2.5 instruct model about 1 month ago
  • tokenizer_config.json
    348 Bytes
    Publish Argonne 2.5 instruct model about 1 month ago