Instructions to use BigTMiami/amazon_pretraining_500k_checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BigTMiami/amazon_pretraining_500k_checkpoints with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BigTMiami/amazon_pretraining_500k_checkpoints")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BigTMiami/amazon_pretraining_500k_checkpoints") model = AutoModelForMaskedLM.from_pretrained("BigTMiami/amazon_pretraining_500k_checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from BigTMiami/amazon_pretraining_500k_checkpoints: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/BigTMiami/amazon_pretraining_500k_checkpoints/resolve/main/training_args.bin
- Command line
-
hf download hf://BigTMiami/amazon_pretraining_500k_checkpoints/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/BigTMiami/amazon_pretraining_500k_checkpoints/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- c56ef605e3eed6eb7aba28c9a338ee0c7a8356b4b06fed6020ad63a1696cf8a0
- Size of remote file:
- 4.92 kB
- SHA256:
- 7c9b2c7b73796fcb7772c2e746f8a34b8a703d5029bde74e5b89bcfe3e23021a
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