Image-to-Text
Transformers
Safetensors
English
paddleocr_vl
image-text-to-text
vision
ocr
medical
paddleocr
unsloth
lora
ernie-challenge
custom_code
Instructions to use naazimsnh02/medocr-vision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use naazimsnh02/medocr-vision with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="naazimsnh02/medocr-vision", trust_remote_code=True)# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("naazimsnh02/medocr-vision", trust_remote_code=True) model = AutoModelForMultimodalLM.from_pretrained("naazimsnh02/medocr-vision", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use naazimsnh02/medocr-vision with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for naazimsnh02/medocr-vision to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for naazimsnh02/medocr-vision to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for naazimsnh02/medocr-vision to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="naazimsnh02/medocr-vision", max_seq_length=2048, )
- Xet hash:
- 04cdbddf4dce991c41a4d621aed8da5a59eb516587013929f082ea591cb000ba
- Size of remote file:
- 1.61 MB
- SHA256:
- 34ef7db83df785924fb83d7b887b6e822a031c56e15cff40aaf9b982988180df
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