Text Classification
Transformers
Safetensors
distilbert
sentiment-analysis
text-embeddings-inference
Instructions to use 92amineee/distilbert-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 92amineee/distilbert-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="92amineee/distilbert-sentiment")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("92amineee/distilbert-sentiment") model = AutoModelForSequenceClassification.from_pretrained("92amineee/distilbert-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from 92amineee/distilbert-sentiment: direct link, hf CLI and curl.
- Browser
- Download file 5.27 kB
-
https://huggingface.co/92amineee/distilbert-sentiment/resolve/main/training_args.bin
- Command line
-
hf download hf://92amineee/distilbert-sentiment/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/92amineee/distilbert-sentiment/resolve/main/training_args.bin
5.27 kB
- Xet hash:
- ee435f6ff30b29523b0aed961641316ed894f02158fd66255e9a0abb440e5219
- Size of remote file:
- 5.27 kB
- SHA256:
- 06f8b23f51d78863e6b464b35e13beabaa277e0d3eadc297a9246b9bcb9486b1
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