Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use gsl22/sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gsl22/sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gsl22/sentiment-analysis")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gsl22/sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("gsl22/sentiment-analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from gsl22/sentiment-analysis: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/gsl22/sentiment-analysis/resolve/main/training_args.bin
- Command line
-
hf download hf://gsl22/sentiment-analysis/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/gsl22/sentiment-analysis/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- a6da8cf1bcc26f2f7b888ae10279fcfde70b8cb82158e6d383e2979848a8c9d6
- Size of remote file:
- 3.96 kB
- SHA256:
- 89212554e9e9023992294619661732c2d3732a98b60d7795ba8afae6626c4381
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