Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use redevaaa/fin1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use redevaaa/fin1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="redevaaa/fin1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("redevaaa/fin1") model = AutoModelForTokenClassification.from_pretrained("redevaaa/fin1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from redevaaa/fin1: direct link, hf CLI and curl.
- Browser
- Download file 3.39 kB
-
https://huggingface.co/redevaaa/fin1/resolve/main/training_args.bin
- Command line
-
hf download hf://redevaaa/fin1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/redevaaa/fin1/resolve/main/training_args.bin
3.39 kB
- Xet hash:
- 63982c48e29dcef52f1a40f2144b23b2d2d00c9f2181de05a18c0a297b73283d
- Size of remote file:
- 3.39 kB
- SHA256:
- 4e62754de47a0e383e6ca3ab1c4d8072e9d668b9105634208339407250cfaa94
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