Instructions to use DemangeJeremy/4-sentiments-with-flaubert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DemangeJeremy/4-sentiments-with-flaubert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DemangeJeremy/4-sentiments-with-flaubert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DemangeJeremy/4-sentiments-with-flaubert") model = AutoModelForSequenceClassification.from_pretrained("DemangeJeremy/4-sentiments-with-flaubert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from DemangeJeremy/4-sentiments-with-flaubert: direct link, hf CLI and curl.
- Browser
- Download file 1.49 GB
-
https://huggingface.co/DemangeJeremy/4-sentiments-with-flaubert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://DemangeJeremy/4-sentiments-with-flaubert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/DemangeJeremy/4-sentiments-with-flaubert/resolve/main/pytorch_model.bin
1.49 GB
- Xet hash:
- 25e6e9917bb5e622df90a988a0e80496599060949a3b4158074b8b60639d0281
- Size of remote file:
- 1.49 GB
- SHA256:
- c443c0b3f13bf06f92091db7bdac7dbbfe7e44ceed7213397bd48b7e91fb2810
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