Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use redevaaa/test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use redevaaa/test2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="redevaaa/test2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("redevaaa/test2") model = AutoModelForTokenClassification.from_pretrained("redevaaa/test2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from redevaaa/test2: direct link, hf CLI and curl.
- Browser
- Download file 3.38 kB
-
https://huggingface.co/redevaaa/test2/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://redevaaa/test2@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/redevaaa/test2/resolve/refs%2Fpr%2F1/training_args.bin
3.38 kB
- Xet hash:
- 0924bfeb9aa49c21ed7ac81a150a241a0e945aa1f3e87a6b5992b78ebbc7dc43
- Size of remote file:
- 3.38 kB
- SHA256:
- 09cfbd8a1b6f8344f9d70186a1816539eff8d1eab169a32ef5d1cb5253a5c103
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