Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use redevaaa/fin6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use redevaaa/fin6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="redevaaa/fin6")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("redevaaa/fin6") model = AutoModelForTokenClassification.from_pretrained("redevaaa/fin6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from redevaaa/fin6: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/redevaaa/fin6/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://redevaaa/fin6/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/redevaaa/fin6/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- ba2aa6b0d88959a6c295d700eecd6f209691119fe1c63d149480419a6ca8e28f
- Size of remote file:
- 431 MB
- SHA256:
- fe4d7eb5a75155563c81c8733b512308fea5cf354b9f6ae031a1d9c90a217904
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