Instructions to use garNER/camembert-base-fr-LM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use garNER/camembert-base-fr-LM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="garNER/camembert-base-fr-LM")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("garNER/camembert-base-fr-LM") model = AutoModelForTokenClassification.from_pretrained("garNER/camembert-base-fr-LM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e1585c7e5a85dc3ba1de723100c5cebe2cb6b08a0bf6322956b2386f5146b4e1
- Size of remote file:
- 440 MB
- SHA256:
- 260f34be6546ea76b66f9dd9bc79b0de6f6a23523cedc4a33974d941427da839
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.