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 last-checkpoint/optimizer.pt from harsith05/imdb_practice: direct link, hf CLI and curl.
- Browser
- Download file 113 MB
-
https://huggingface.co/harsith05/imdb_practice/resolve/main/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://harsith05/imdb_practice/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/harsith05/imdb_practice/resolve/main/last-checkpoint/optimizer.pt
113 MB
- Xet hash:
- cff80a612a263f941f610325413e6505386b5eb7682ecce14b0b46099a96468a
- Size of remote file:
- 113 MB
- SHA256:
- 25e621d5cf97ecffb7ae94371944f0b9b0bb7020ee696a7d5a556284120f795d
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