Instructions to use Shraddha257/1GENReviewsSentimentSamples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shraddha257/1GENReviewsSentimentSamples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Shraddha257/1GENReviewsSentimentSamples")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Shraddha257/1GENReviewsSentimentSamples") model = AutoModelForSequenceClassification.from_pretrained("Shraddha257/1GENReviewsSentimentSamples", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Shraddha257/1GENReviewsSentimentSamples: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/Shraddha257/1GENReviewsSentimentSamples/resolve/main/training_args.bin
- Command line
-
hf download hf://Shraddha257/1GENReviewsSentimentSamples/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Shraddha257/1GENReviewsSentimentSamples/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- ab2f7383e26279a4589c8ecbbe57914901a4f6e9b43f00950d8d7cdf7cda37b4
- Size of remote file:
- 4.73 kB
- SHA256:
- c395ef5edd98861746bd66334aaf8693c8ab4356399ad85e76376be37e1e7473
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