Instructions to use SajilAwale/FunnyModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SajilAwale/FunnyModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SajilAwale/FunnyModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SajilAwale/FunnyModel") model = AutoModelForSequenceClassification.from_pretrained("SajilAwale/FunnyModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from SajilAwale/FunnyModel: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/SajilAwale/FunnyModel/resolve/b3fe35e852dd4db65bfb8ca6c3f9c215c2a8e180/training_args.bin
- Command line
-
hf download hf://SajilAwale/FunnyModel@b3fe35e852dd4db65bfb8ca6c3f9c215c2a8e180/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/SajilAwale/FunnyModel/resolve/b3fe35e852dd4db65bfb8ca6c3f9c215c2a8e180/training_args.bin
5.37 kB
- Xet hash:
- 98a781392167030b84b5a2b3b3b69877838db7aa07e66b77d007aa4b3b556c49
- Size of remote file:
- 5.37 kB
- SHA256:
- 35531673e20e0f09fd3162c7b6368e6a29055758573807e35378eeff5256983a
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