Instructions to use AliChazz/bert-sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AliChazz/bert-sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AliChazz/bert-sentiment-analysis")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AliChazz/bert-sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("AliChazz/bert-sentiment-analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from AliChazz/bert-sentiment-analysis: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/AliChazz/bert-sentiment-analysis/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://AliChazz/bert-sentiment-analysis/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/AliChazz/bert-sentiment-analysis/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 23a467326bf982fd69d5f5d5089cc1cc4cb73a27877b475c2cf62075d509bc55
- Size of remote file:
- 438 MB
- SHA256:
- e3e201559bea4fade6d89bad2cca62b53d621375a8ca8b89d4a49fadef63a9b2
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