Instructions to use KeviniveK/CustomModel_IMDB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KeviniveK/CustomModel_IMDB with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KeviniveK/CustomModel_IMDB")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KeviniveK/CustomModel_IMDB") model = AutoModelForSequenceClassification.from_pretrained("KeviniveK/CustomModel_IMDB", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from KeviniveK/CustomModel_IMDB: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/KeviniveK/CustomModel_IMDB/resolve/main/model.safetensors
- Command line
-
hf download hf://KeviniveK/CustomModel_IMDB/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/KeviniveK/CustomModel_IMDB/resolve/main/model.safetensors
268 MB
- Xet hash:
- 92f4d665ec08202352c910ab3d98ef55cdd6bdd229bba4ba8d91214f9d47584e
- Size of remote file:
- 268 MB
- SHA256:
- e359745d7a075f1b5d7d6ff3d39cf1793bb07b581e8e70c90865538bb0c504b0
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