Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Jedida/sentence_sentiments_analysis_distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jedida/sentence_sentiments_analysis_distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jedida/sentence_sentiments_analysis_distilbert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jedida/sentence_sentiments_analysis_distilbert") model = AutoModelForSequenceClassification.from_pretrained("Jedida/sentence_sentiments_analysis_distilbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Jedida/sentence_sentiments_analysis_distilbert: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/Jedida/sentence_sentiments_analysis_distilbert/resolve/main/training_args.bin
- Command line
-
hf download hf://Jedida/sentence_sentiments_analysis_distilbert/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Jedida/sentence_sentiments_analysis_distilbert/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 8c4639a53c09c734155dc54f3ce0b01bfd7ac14d30818cf384be2ba8c63967ff
- Size of remote file:
- 4.09 kB
- SHA256:
- 0c47e6ca9a3c5bd85097441b5911f062a91a200aaba0fdd8983c80846356220e
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