Instructions to use bvantuan/camembert-mwer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bvantuan/camembert-mwer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="bvantuan/camembert-mwer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("bvantuan/camembert-mwer") model = AutoModelForTokenClassification.from_pretrained("bvantuan/camembert-mwer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (09146851fef3a50d7f835e32b07e9e5a487f2a2c) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>1be8f85
-
Update config.json
0f6f9bf -
Update README.md
346b4fe -
Update README.md
db2bd59 -
Upload TFCamembertForTokenClassification
ecfecf0 -
Upload tokenizer
bed8d61 -
Upload CamembertForTokenClassification
4e600c2 -
initial commit
a3f14d1