Token Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
Instructions to use Ben10x/tutorial_wnut_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ben10x/tutorial_wnut_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Ben10x/tutorial_wnut_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Ben10x/tutorial_wnut_model") model = AutoModelForTokenClassification.from_pretrained("Ben10x/tutorial_wnut_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Ben10x/tutorial_wnut_model: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/Ben10x/tutorial_wnut_model/resolve/main/training_args.bin
- Command line
-
hf download hf://Ben10x/tutorial_wnut_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Ben10x/tutorial_wnut_model/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- d636c4c582fe7ec4c9404157f03380b4fa42b822f47c4e1ad34169391781f4eb
- Size of remote file:
- 5.37 kB
- SHA256:
- e1df240f27c4006c88f381a615e8345cf3ddec82c333832677dcc1b9727febf8
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