Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use redevaaa/fin3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use redevaaa/fin3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="redevaaa/fin3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("redevaaa/fin3") model = AutoModelForTokenClassification.from_pretrained("redevaaa/fin3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from redevaaa/fin3: direct link, hf CLI and curl.
- Browser
- Download file 3.39 kB
-
https://huggingface.co/redevaaa/fin3/resolve/refs%2Fpr%2F2/training_args.bin
- Command line
-
hf download hf://redevaaa/fin3@refs/pr/2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/redevaaa/fin3/resolve/refs%2Fpr%2F2/training_args.bin
3.39 kB
- Xet hash:
- 5acfccc2e5f8beefe992afb34214582cc23e47ceac9a4baf39d29296ac5d519a
- Size of remote file:
- 3.39 kB
- SHA256:
- 3250482060df8312cc64fb23b791ff48321ac108c6a2c4f0cf0cb6f7f734fe33
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