Feature Extraction
Transformers
PyTorch
TensorFlow
TensorBoard
Safetensors
French
deberta-v2
deberta-v3
debertav2
debertav3
camembert
text-embeddings-inference
Instructions to use almanach/camembertav2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use almanach/camembertav2-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="almanach/camembertav2-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("almanach/camembertav2-base") model = AutoModel.from_pretrained("almanach/camembertav2-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from almanach/camembertav2-base: direct link, hf CLI and curl.
- Browser
- Download file 756 kB
-
https://huggingface.co/almanach/camembertav2-base/resolve/main/tokenizer.json
- Command line
-
hf download hf://almanach/camembertav2-base/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/almanach/camembertav2-base/resolve/main/tokenizer.json
756 kB
File too large to display, you can check the raw version instead.