Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use redevaaa/fin4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use redevaaa/fin4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="redevaaa/fin4")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("redevaaa/fin4") model = AutoModelForTokenClassification.from_pretrained("redevaaa/fin4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from redevaaa/fin4: direct link, hf CLI and curl.
- Browser
- Download file 3.39 kB
-
https://huggingface.co/redevaaa/fin4/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://redevaaa/fin4@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/redevaaa/fin4/resolve/refs%2Fpr%2F1/training_args.bin
3.39 kB
- Xet hash:
- f14cbe8c0397ecc677d4e194f802a5f48d8cb08767c5e35d7a7b07380e551277
- Size of remote file:
- 3.39 kB
- SHA256:
- 31d4b2484477584028d6bf3c18e80877b59be2ebcdb2985ef5f018bf7431a014
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