Instructions to use noodlesFelicity/content with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use noodlesFelicity/content with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="noodlesFelicity/content")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("noodlesFelicity/content") model = AutoModelForMaskedLM.from_pretrained("noodlesFelicity/content", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from noodlesFelicity/content: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/noodlesFelicity/content/resolve/main/training_args.bin
- Command line
-
hf download hf://noodlesFelicity/content/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/noodlesFelicity/content/resolve/main/training_args.bin
3.31 kB
- Xet hash:
- a6b643b9dce356bdd21588cf9bbdecb3b947d45b7ae2a77e09822f0f3e08f3aa
- Size of remote file:
- 3.31 kB
- SHA256:
- a80a510e0dc292b1db9703ab6c6dcca2d0bb878fa35774788a98c84840abcfab
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