Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use redevaaa/test4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use redevaaa/test4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="redevaaa/test4")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("redevaaa/test4") model = AutoModelForTokenClassification.from_pretrained("redevaaa/test4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from redevaaa/test4: direct link, hf CLI and curl.
- Browser
- Download file 3.38 kB
-
https://huggingface.co/redevaaa/test4/resolve/main/training_args.bin
- Command line
-
hf download hf://redevaaa/test4/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/redevaaa/test4/resolve/main/training_args.bin
3.38 kB
- Xet hash:
- f03315185ae0c702dae590ef8e68e7a2b71699ea108b41ca61fa8121debcadf0
- Size of remote file:
- 3.38 kB
- SHA256:
- c6321bec65a7efaf83e884beb2bed7d42d03901c8a3f3ef898e3d26189cdf5b1
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