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Infi-MM
/
infimm-hd

Text Generation
Transformers
PyTorch
English
infimm-hd
multimodal
text
image
image-to-text
conversational
custom_code
Model card Files Files and versions
xet
Community
1

Instructions to use Infi-MM/infimm-hd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Infi-MM/infimm-hd with Transformers:

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

    How to use Infi-MM/infimm-hd with vLLM:

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

    How to use Infi-MM/infimm-hd 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 "Infi-MM/infimm-hd" \
        --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": "Infi-MM/infimm-hd",
    		"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 "Infi-MM/infimm-hd" \
            --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": "Infi-MM/infimm-hd",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use Infi-MM/infimm-hd with Docker Model Runner:

    docker model run hf.co/Infi-MM/infimm-hd
infimm-hd
36 GB
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  • 3 contributors
History: 15 commits
lllliuhhhhggg's picture
lllliuhhhhggg
Update README.md
c20153b verified about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • LICENSE
    19.9 kB
    Create LICENSE about 2 years ago
  • README.md
    2.34 kB
    Update README.md about 2 years ago
  • added_tokens.json
    50 Bytes
    first commit about 2 years ago
  • config.json
    1.77 kB
    first commit about 2 years ago
  • configuration_infimm_hd.py
    1.35 kB
    first commit about 2 years ago
  • eva_vit_model.py
    28.9 kB
    Update eva_vit_model.py about 2 years ago
  • flamingo.py
    13.6 kB
    first commit about 2 years ago
  • flamingo_lm.py
    15.2 kB
    first commit about 2 years ago
  • modeling_infimm_hd.py
    4.63 kB
    first commit about 2 years ago
  • modules.py
    8 kB
    first commit about 2 years ago
  • preprocessor_config.json
    143 Bytes
    first commit about 2 years ago
  • processing_infimm_hd.py
    15.4 kB
    first commit about 2 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

    • "torch.BFloat16Storage",
    • "torch._utils._rebuild_tensor_v2",
    • "collections.OrderedDict"

    What is a pickle import?

    36 GB
    xet
    first commit about 2 years ago
  • special_tokens_map.json
    878 Bytes
    first commit about 2 years ago
  • tokenizer.model
    500 kB
    xet
    first commit about 2 years ago
  • tokenizer_config.json
    2.27 kB
    first commit about 2 years ago
  • utils.py
    3.82 kB
    first commit about 2 years ago