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 training_args.bin from redevaaa/fin6: direct link, hf CLI and curl.
- Browser
- Download file 3.39 kB
-
https://huggingface.co/redevaaa/fin6/resolve/main/training_args.bin
- Command line
-
hf download hf://redevaaa/fin6/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/redevaaa/fin6/resolve/main/training_args.bin
3.39 kB
- Xet hash:
- c45d7763e576d69f0e308f1d15eb850d3967f1d1855de66a98e46fd11e42f9c3
- Size of remote file:
- 3.39 kB
- SHA256:
- 0fa9551ac52e50a8fd3f2f433239a2594861fa924e58c3611c8fda16eadbd9f9
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