Instructions to use TeeA/DEPLOT-ViChart-word with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TeeA/DEPLOT-ViChart-word with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="TeeA/DEPLOT-ViChart-word")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("TeeA/DEPLOT-ViChart-word") model = AutoModelForMultimodalLM.from_pretrained("TeeA/DEPLOT-ViChart-word", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use TeeA/DEPLOT-ViChart-word with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TeeA/DEPLOT-ViChart-word" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TeeA/DEPLOT-ViChart-word", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/TeeA/DEPLOT-ViChart-word
- SGLang
How to use TeeA/DEPLOT-ViChart-word 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 "TeeA/DEPLOT-ViChart-word" \ --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": "TeeA/DEPLOT-ViChart-word", "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 "TeeA/DEPLOT-ViChart-word" \ --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": "TeeA/DEPLOT-ViChart-word", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use TeeA/DEPLOT-ViChart-word with Docker Model Runner:
docker model run hf.co/TeeA/DEPLOT-ViChart-word
Upload Pix2StructForConditionalGeneration
Browse files- config.json +1 -1
- model.safetensors +2 -2
config.json
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"encoder_hidden_size": 768,
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"initializer_range": 0.02,
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"model_type": "pix2struct_text_model",
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"vocab_size":
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},
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"tie_word_embeddings": false,
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"torch_dtype": "float32",
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"encoder_hidden_size": 768,
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"initializer_range": 0.02,
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"model_type": "pix2struct_text_model",
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"vocab_size": 36098
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},
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"tie_word_embeddings": false,
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"torch_dtype": "float32",
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 1042264896
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