Text Classification
Transformers
PyTorch
TensorFlow
Rust
Safetensors
English
distilbert
Eval Results (legacy)
Instructions to use HARSHU550/Sentiments with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HARSHU550/Sentiments with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HARSHU550/Sentiments")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HARSHU550/Sentiments") model = AutoModelForSequenceClassification.from_pretrained("HARSHU550/Sentiments", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from HARSHU550/Sentiments: direct link, hf CLI and curl.
- Browser
- Download file 48 Bytes
-
https://huggingface.co/HARSHU550/Sentiments/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://HARSHU550/Sentiments/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/HARSHU550/Sentiments/resolve/main/tokenizer_config.json
48 Bytes
| {"model_max_length": 512, "do_lower_case": true} |