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anaghasavit
/
ocr30000

Image-Text-to-Text
Transformers
PyTorch
TensorBoard
vision-encoder-decoder
Generated from Trainer
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use anaghasavit/ocr30000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use anaghasavit/ocr30000 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-text-to-text", model="anaghasavit/ocr30000")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForImageTextToText
    
    tokenizer = AutoTokenizer.from_pretrained("anaghasavit/ocr30000")
    model = AutoModelForImageTextToText.from_pretrained("anaghasavit/ocr30000")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use anaghasavit/ocr30000 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "anaghasavit/ocr30000"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "anaghasavit/ocr30000",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/anaghasavit/ocr30000
  • SGLang

    How to use anaghasavit/ocr30000 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 "anaghasavit/ocr30000" \
        --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": "anaghasavit/ocr30000",
    		"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 "anaghasavit/ocr30000" \
            --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": "anaghasavit/ocr30000",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use anaghasavit/ocr30000 with Docker Model Runner:

    docker model run hf.co/anaghasavit/ocr30000
ocr30000
1.54 GB
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  • 1 contributor
History: 7 commits
anaghasavit's picture
anaghasavit
End of training
05bf82b about 3 years ago
  • runs
    Model save about 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • .gitignore
    13 Bytes
    Training in progress, step 1000 about 3 years ago
  • README.md
    1.44 kB
    update model card README.md about 3 years ago
  • all_results.json
    207 Bytes
    End of training about 3 years ago
  • config.json
    4.87 kB
    Training in progress, step 1000 about 3 years ago
  • generation_config.json
    273 Bytes
    Model save about 3 years ago
  • preprocessor_config.json
    325 Bytes
    Training in progress, step 1000 about 3 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    1.54 GB
    xet
    Model save about 3 years ago
  • train_results.json
    207 Bytes
    End of training about 3 years ago
  • trainer_state.json
    202 kB
    End of training about 3 years ago
  • training_args.bin

    Detected Pickle imports (6)

    • "transformers.trainer_utils.SchedulerType",
    • "transformers.trainer_utils.IntervalStrategy",
    • "transformers.training_args_seq2seq.Seq2SeqTrainingArguments",
    • "transformers.training_args.OptimizerNames",
    • "torch.device",
    • "transformers.trainer_utils.HubStrategy"

    How to fix it?

    3.64 kB
    xet
    Training in progress, step 1000 about 3 years ago