Feature Extraction
Transformers
TensorFlow
TensorBoard
camembert
generated_from_keras_callback
text-embeddings-inference
Instructions to use RubenBueno/camembert-base-finetuned-text-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RubenBueno/camembert-base-finetuned-text-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="RubenBueno/camembert-base-finetuned-text-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("RubenBueno/camembert-base-finetuned-text-classification") model = AutoModel.from_pretrained("RubenBueno/camembert-base-finetuned-text-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from RubenBueno/camembert-base-finetuned-text-classification: direct link, hf CLI and curl.
- Browser
- Download file 28 Bytes
-
https://huggingface.co/RubenBueno/camembert-base-finetuned-text-classification/resolve/main/added_tokens.json
- Command line
-
hf download hf://RubenBueno/camembert-base-finetuned-text-classification/added_tokens.json
-
curl -L -o added_tokens.json https://huggingface.co/RubenBueno/camembert-base-finetuned-text-classification/resolve/main/added_tokens.json
28 Bytes
| { | |
| "<unk>NOTUSED": 32005 | |
| } | |