Instructions to use pvbhanuteja/llmv3-base-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pvbhanuteja/llmv3-base-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="pvbhanuteja/llmv3-base-funsd")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("pvbhanuteja/llmv3-base-funsd") model = AutoModelForTokenClassification.from_pretrained("pvbhanuteja/llmv3-base-funsd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 661c8963e83ec24823771795b894fdb5d7fcd1f4544da105894292590d83e411
- Size of remote file:
- 501 MB
- SHA256:
- 227aa1cedf5b51f1070775c42769afe2a5475785720ee5970b170c6dc12cb0b4
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