Instructions to use Nadav/camembert-base-squad-fr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nadav/camembert-base-squad-fr with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="Nadav/camembert-base-squad-fr")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Nadav/camembert-base-squad-fr") model = AutoModelForQuestionAnswering.from_pretrained("Nadav/camembert-base-squad-fr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Nadav/camembert-base-squad-fr: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/Nadav/camembert-base-squad-fr/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Nadav/camembert-base-squad-fr/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Nadav/camembert-base-squad-fr/resolve/main/pytorch_model.bin
440 MB
- Xet hash:
- 05c5048e4090f6388eb6c19706c3a98f57bb4ba21623659d0adf6e632c8efc18
- Size of remote file:
- 440 MB
- SHA256:
- b0666b3232b208c6c4190831f7a5ceba12ede1d4fb7943440ac497e542fedb9f
路
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