Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use redevaaa/fin5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use redevaaa/fin5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="redevaaa/fin5")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("redevaaa/fin5") model = AutoModelForTokenClassification.from_pretrained("redevaaa/fin5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from redevaaa/fin5: direct link, hf CLI and curl.
- Browser
- Download file 3.39 kB
-
https://huggingface.co/redevaaa/fin5/resolve/main/training_args.bin
- Command line
-
hf download hf://redevaaa/fin5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/redevaaa/fin5/resolve/main/training_args.bin
3.39 kB
- Xet hash:
- 9edf38043ad8376d50c6334e1e5a4763e673f3b251cab7f0432ef96a15bfe4a4
- Size of remote file:
- 3.39 kB
- SHA256:
- 2d7b53a8f1545597e3179a1a71747a023a37025d4c224056f427c486084abe57
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