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 pytorch_model.bin from redevaaa/fin4: direct link, hf CLI and curl.
- Browser
- Download file 434 MB
-
https://huggingface.co/redevaaa/fin4/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://redevaaa/fin4/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/redevaaa/fin4/resolve/main/pytorch_model.bin
434 MB
- Xet hash:
- 7b75fce4c9bbcdf4d48b0e152a9ce4aa0e1c58eb372e571a9d0f1c082b283ed7
- Size of remote file:
- 434 MB
- SHA256:
- 441e4f8cae5f5cd5751092076f7d7822032ab7868541fc39bc9225f162dfa7ac
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