Instructions to use GhylB/Sentiment_Analysis_DistilBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GhylB/Sentiment_Analysis_DistilBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GhylB/Sentiment_Analysis_DistilBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("GhylB/Sentiment_Analysis_DistilBERT") model = AutoModelForSequenceClassification.from_pretrained("GhylB/Sentiment_Analysis_DistilBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from GhylB/Sentiment_Analysis_DistilBERT: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/GhylB/Sentiment_Analysis_DistilBERT/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://GhylB/Sentiment_Analysis_DistilBERT@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/GhylB/Sentiment_Analysis_DistilBERT/resolve/refs%2Fpr%2F1/pytorch_model.bin
268 MB
- Xet hash:
- 6fd44820dbd8db1cb6a88df422bf904cd6175d002eaffbd931ce3db09567d10d
- Size of remote file:
- 268 MB
- SHA256:
- 76f45af0e1524ff45ec7cca033620ba5e9643bc3795d7489aebd7c2d5adcc8f7
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