Instructions to use BigTMiami/amazon_pretraining_5M_model_corrected with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BigTMiami/amazon_pretraining_5M_model_corrected with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BigTMiami/amazon_pretraining_5M_model_corrected")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BigTMiami/amazon_pretraining_5M_model_corrected") model = AutoModelForMaskedLM.from_pretrained("BigTMiami/amazon_pretraining_5M_model_corrected", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from BigTMiami/amazon_pretraining_5M_model_corrected: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/BigTMiami/amazon_pretraining_5M_model_corrected/resolve/main/training_args.bin
- Command line
-
hf download hf://BigTMiami/amazon_pretraining_5M_model_corrected/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/BigTMiami/amazon_pretraining_5M_model_corrected/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 1f6a997138b301be87ec5c5a48195402fd2cc89acf4d6d04c98cb347afa4ee54
- Size of remote file:
- 4.92 kB
- SHA256:
- e8a050b5b842b53b732a7194fc770d6d68af1e0c2cf5093c393528e9e5afa65a
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