Instructions to use Muhammad7777/e5-small-v2-sentiment-twitter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Muhammad7777/e5-small-v2-sentiment-twitter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Muhammad7777/e5-small-v2-sentiment-twitter")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Muhammad7777/e5-small-v2-sentiment-twitter") model = AutoModelForSequenceClassification.from_pretrained("Muhammad7777/e5-small-v2-sentiment-twitter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Muhammad7777/e5-small-v2-sentiment-twitter: direct link, hf CLI and curl.
- Browser
- Download file 5.84 kB
-
https://huggingface.co/Muhammad7777/e5-small-v2-sentiment-twitter/resolve/main/training_args.bin
- Command line
-
hf download hf://Muhammad7777/e5-small-v2-sentiment-twitter/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Muhammad7777/e5-small-v2-sentiment-twitter/resolve/main/training_args.bin
5.84 kB
- Xet hash:
- 6d611c28939cfd7d4b557da4c9fefedf929d26943da6b682256972f900b2bb1b
- Size of remote file:
- 5.84 kB
- SHA256:
- 271dcaa78133386591779b8cd05b30dbff98dbd0a38f45c8747f7bcaae23410d
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