Text Classification
Transformers
Safetensors
distilbert
sentiment-analysis
bert
goemotions
nlp
text-embeddings-inference
Instructions to use Krish623/sentiment-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Krish623/sentiment-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Krish623/sentiment-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Krish623/sentiment-model") model = AutoModelForSequenceClassification.from_pretrained("Krish623/sentiment-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Krish623/sentiment-model: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/Krish623/sentiment-model/resolve/main/tokenizer.json
- Command line
-
hf download hf://Krish623/sentiment-model/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Krish623/sentiment-model/resolve/main/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.