Text Classification
Transformers
distilbert
sentiment-analysis
3-class
roberta
text-embeddings-inference
Instructions to use MayAmb/distilbert-3class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MayAmb/distilbert-3class with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MayAmb/distilbert-3class")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MayAmb/distilbert-3class") model = AutoModelForSequenceClassification.from_pretrained("MayAmb/distilbert-3class", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from MayAmb/distilbert-3class: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/MayAmb/distilbert-3class/resolve/main/tokenizer.json
- Command line
-
hf download hf://MayAmb/distilbert-3class/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/MayAmb/distilbert-3class/resolve/main/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.