Text Classification
Transformers
TensorBoard
Safetensors
French
deberta-v2
review-classification
Eval Results (legacy)
text-embeddings-inference
Instructions to use almanach/camembertav2-base-cls with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use almanach/camembertav2-base-cls with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="almanach/camembertav2-base-cls")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("almanach/camembertav2-base-cls") model = AutoModelForSequenceClassification.from_pretrained("almanach/camembertav2-base-cls", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from almanach/camembertav2-base-cls: direct link, hf CLI and curl.
- Browser
- Download file 5.56 kB
-
https://huggingface.co/almanach/camembertav2-base-cls/resolve/main/training_args.bin
- Command line
-
hf download hf://almanach/camembertav2-base-cls/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/almanach/camembertav2-base-cls/resolve/main/training_args.bin
5.56 kB
- Xet hash:
- e06d4d10e6f8930a8abe0df24d696936aff3f23d1afa81254276d432838cc0bf
- Size of remote file:
- 5.56 kB
- SHA256:
- 0cbabdbec06e222418e949caaf387e771ff57de22ba0d18efc939af09fb1f22f
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