Instructions to use AG/pretraining with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AG/pretraining with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="AG/pretraining")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("AG/pretraining") model = AutoModel.from_pretrained("AG/pretraining", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from AG/pretraining: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/AG/pretraining/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://AG/pretraining/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/AG/pretraining/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- a5624301bd11fece392b130053b14d7deae7c620078faa13a1317680c6e5dfd9
- Size of remote file:
- 499 MB
- SHA256:
- 02db7633096d6eb0d26bf4bfde8612369c51895660ea516fde22e258865a3033
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