Instructions to use ghost12/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ghost12/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ghost12/my_awesome_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ghost12/my_awesome_model") model = AutoModelForSequenceClassification.from_pretrained("ghost12/my_awesome_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ghost12/my_awesome_model: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/ghost12/my_awesome_model/resolve/main/training_args.bin
- Command line
-
hf download hf://ghost12/my_awesome_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ghost12/my_awesome_model/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- df27de56217d6db35b44120c2469ad06cc48d01feafae5fb7208dd54077ed949
- Size of remote file:
- 4.92 kB
- SHA256:
- a818c4303ab6d9db31abfd2d98616936f482dc54173d844ac24928b5552da23f
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