Token Classification
Transformers
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
Instructions to use krishnareddy/hello_token_classification_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use krishnareddy/hello_token_classification_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="krishnareddy/hello_token_classification_model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("krishnareddy/hello_token_classification_model") model = AutoModelForTokenClassification.from_pretrained("krishnareddy/hello_token_classification_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd7e9ff5cbc349c0a2c04b64e2d3550d8fb8c57f20af259430ca689e2ba469ca
- Size of remote file:
- 4.6 kB
- SHA256:
- e7ca585ef08a7f8299a14dca7cd3ce91a9defc42436e3c3f63f2589da5bc4af5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.