Instructions to use Bugpie/dummy-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bugpie/dummy-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Bugpie/dummy-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Bugpie/dummy-model") model = AutoModelForMaskedLM.from_pretrained("Bugpie/dummy-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -7,11 +7,11 @@ datasets:
|
|
| 7 |
|
| 8 |
## Model description
|
| 9 |
|
| 10 |
-
CamemBERT is a state-of-the-art language model for French based on the RoBERTa model.
|
| 11 |
|
| 12 |
-
|
| 13 |
|
| 14 |
-
|
| 15 |
|
| 16 |
## How to use
|
| 17 |
|
|
|
|
| 7 |
|
| 8 |
## Model description
|
| 9 |
|
| 10 |
+
CamemBERT is a state-of-the-art language model for French based on the RoBERTa model. It is now available on Hugging Face in 6 different versions with varying number of parameters, amount of pretraining data and pretraining data source domains.
|
| 11 |
|
| 12 |
+
## Evaluation
|
| 13 |
|
| 14 |
+
The model developers evaluated CamemBERT using four different downstream tasks for French: part-of-speech (POS) tagging, dependency parsing, named entity recognition (NER) and natural language inference (NLI).
|
| 15 |
|
| 16 |
## How to use
|
| 17 |
|