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 pytorch_model.bin from noodlesFelicity/content: direct link, hf CLI and curl.
- Browser
- Download file 140 MB
-
https://huggingface.co/noodlesFelicity/content/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://noodlesFelicity/content/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/noodlesFelicity/content/resolve/main/pytorch_model.bin
140 MB
- Xet hash:
- 14d4ca6de5b76ea8dedd1acfffff9b645338cbe8bda439ce009eb5fed6010f57
- Size of remote file:
- 140 MB
- SHA256:
- 99642699fd337dae4908ab32f49761f943067e9829276380c22e46423f51e1bf
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