Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use rlimonta/sentiment_analysis_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rlimonta/sentiment_analysis_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rlimonta/sentiment_analysis_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rlimonta/sentiment_analysis_model") model = AutoModelForSequenceClassification.from_pretrained("rlimonta/sentiment_analysis_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from rlimonta/sentiment_analysis_model: direct link, hf CLI and curl.
- Browser
- Download file 5.84 kB
-
https://huggingface.co/rlimonta/sentiment_analysis_model/resolve/main/training_args.bin
- Command line
-
hf download hf://rlimonta/sentiment_analysis_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/rlimonta/sentiment_analysis_model/resolve/main/training_args.bin
5.84 kB
- Xet hash:
- 3446d1263f9d1c9d5fb6a7ea184c2da0525fb28dccbd6a662c8cffe4197c6ff3
- Size of remote file:
- 5.84 kB
- SHA256:
- 0dbb11d73f89fcbe3c9eea3fc947e61aa57afa0d2ca4f9c3fdf39e2347a56085
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