Text Classification
Transformers
Safetensors
French
English
deberta-v2
name
person
company
deprecated
text-embeddings-inference
Instructions to use ele-sage/camembertav2-base-name-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ele-sage/camembertav2-base-name-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ele-sage/camembertav2-base-name-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ele-sage/camembertav2-base-name-classifier") model = AutoModelForSequenceClassification.from_pretrained("ele-sage/camembertav2-base-name-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ele-sage/camembertav2-base-name-classifier: direct link, hf CLI and curl.
- Browser
- Download file 5.84 kB
-
https://huggingface.co/ele-sage/camembertav2-base-name-classifier/resolve/main/training_args.bin
- Command line
-
hf download hf://ele-sage/camembertav2-base-name-classifier/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ele-sage/camembertav2-base-name-classifier/resolve/main/training_args.bin
5.84 kB
- Xet hash:
- c362182c8c84b6b837d08e8e9f2484e9fae6a9caf56f1b6b3bc081cd4c36257c
- Size of remote file:
- 5.84 kB
- SHA256:
- c15d85fc995f0d8f7dd80edc05e5ebfc79908cf354541b6b08475852720d9e18
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