Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use redevaaa/fin2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use redevaaa/fin2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="redevaaa/fin2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("redevaaa/fin2") model = AutoModelForTokenClassification.from_pretrained("redevaaa/fin2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from redevaaa/fin2: direct link, hf CLI and curl.
- Browser
- Download file 434 MB
-
https://huggingface.co/redevaaa/fin2/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://redevaaa/fin2@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/redevaaa/fin2/resolve/refs%2Fpr%2F1/pytorch_model.bin
434 MB
- Xet hash:
- 87c233a65b6050606160bd50fdfa20a3f8587a8e11a3816a906a485dd5b20327
- Size of remote file:
- 434 MB
- SHA256:
- 8ff4d6229ca2d657376aabc853892fe7294ed0c416f681fa05ad3edf39eba240
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