Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Laurie/sentiment-classify with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Laurie/sentiment-classify with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Laurie/sentiment-classify")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Laurie/sentiment-classify") model = AutoModelForSequenceClassification.from_pretrained("Laurie/sentiment-classify", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Laurie/sentiment-classify: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/Laurie/sentiment-classify/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Laurie/sentiment-classify/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Laurie/sentiment-classify/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 251fe42c48d39cf48ec69feea5f66c71eb6571b65ed6547ad641162168a647c2
- Size of remote file:
- 268 MB
- SHA256:
- 86ca91f40c56870af67eae344101ee8367f851c00b2bc941d044aa65b2e17e9a
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