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 training_args.bin from Laurie/sentiment-classify: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/Laurie/sentiment-classify/resolve/main/training_args.bin
- Command line
-
hf download hf://Laurie/sentiment-classify/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Laurie/sentiment-classify/resolve/main/training_args.bin
3.31 kB
- Xet hash:
- 2357104a2939a7d9c19bf6bd8bbc8ecbe5f5960c2ee335cf5fa4eba621169e4f
- Size of remote file:
- 3.31 kB
- SHA256:
- 64ce4686a410da626ad4dce530f517300f9b66f7f460194a7b3f0b14c53ba1d7
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