Instructions to use AnkitAI/reviews-roberta-base-sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnkitAI/reviews-roberta-base-sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnkitAI/reviews-roberta-base-sentiment-analysis")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnkitAI/reviews-roberta-base-sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("AnkitAI/reviews-roberta-base-sentiment-analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from AnkitAI/reviews-roberta-base-sentiment-analysis: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/AnkitAI/reviews-roberta-base-sentiment-analysis/resolve/main/model.safetensors
- Command line
-
hf download hf://AnkitAI/reviews-roberta-base-sentiment-analysis/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/AnkitAI/reviews-roberta-base-sentiment-analysis/resolve/main/model.safetensors
499 MB
- Xet hash:
- 4eceb29b76e48acd17ea52afbc6eb9386f6c0cb451097a738cb0c590137840ca
- Size of remote file:
- 499 MB
- SHA256:
- 5206855ce74e1b4249b50b4c00db994d8a250e8e965e17be8c17d0490f511188
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.