Text Classification
Transformers
PyTorch
English
distilbert
fill-mask
legal
PyTorch
sentiment-analysis
text-embeddings-inference
Instructions to use ajinathgh/sentiment_analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ajinathgh/sentiment_analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ajinathgh/sentiment_analysis")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ajinathgh/sentiment_analysis") model = AutoModelForMaskedLM.from_pretrained("ajinathgh/sentiment_analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ajinathgh/sentiment_analysis: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/ajinathgh/sentiment_analysis/resolve/refs%2Fpr%2F2/tokenizer.json
- Command line
-
hf download hf://ajinathgh/sentiment_analysis@refs/pr/2/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/ajinathgh/sentiment_analysis/resolve/refs%2Fpr%2F2/tokenizer.json
711 kB
File too large to display, you can check the raw version instead.