Instructions to use BigTMiami/tapt_helpfulness_base_pretraining_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BigTMiami/tapt_helpfulness_base_pretraining_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BigTMiami/tapt_helpfulness_base_pretraining_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BigTMiami/tapt_helpfulness_base_pretraining_model") model = AutoModelForMaskedLM.from_pretrained("BigTMiami/tapt_helpfulness_base_pretraining_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from BigTMiami/tapt_helpfulness_base_pretraining_model: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/BigTMiami/tapt_helpfulness_base_pretraining_model/resolve/main/training_args.bin
- Command line
-
hf download hf://BigTMiami/tapt_helpfulness_base_pretraining_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/BigTMiami/tapt_helpfulness_base_pretraining_model/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 081419143ab6d5b1d3cd35a6db3685259ec2db1f9363fda145f960680689b584
- Size of remote file:
- 4.92 kB
- SHA256:
- b098bcff188b697b9f4d885f511c75a63953a3b13b3fd345a21a8d1169aac2d2
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