Instructions to use harsith05/imdb_practice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harsith05/imdb_practice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="harsith05/imdb_practice")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("harsith05/imdb_practice") model = AutoModelForSequenceClassification.from_pretrained("harsith05/imdb_practice", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from harsith05/imdb_practice: direct link, hf CLI and curl.
- Browser
- Download file 5.2 kB
-
https://huggingface.co/harsith05/imdb_practice/resolve/main/training_args.bin
- Command line
-
hf download hf://harsith05/imdb_practice/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/harsith05/imdb_practice/resolve/main/training_args.bin
5.2 kB
- Xet hash:
- d0b3788b7cd47e9df0c6087bf4ca30ec12b84b1606e0b9d9856d29f7a42a5dc5
- Size of remote file:
- 5.2 kB
- SHA256:
- d6f7c8c0e586aecd45767a6c0c15eccc719251af72a868dcb87d11c5df659bba
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