Instructions to use drhead/long_clip_diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use drhead/long_clip_diffusers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="drhead/long_clip_diffusers")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("drhead/long_clip_diffusers") model = AutoModel.from_pretrained("drhead/long_clip_diffusers", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from drhead/long_clip_diffusers: direct link, hf CLI and curl.
- Browser
- Download file 493 MB
-
https://huggingface.co/drhead/long_clip_diffusers/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://drhead/long_clip_diffusers/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/drhead/long_clip_diffusers/resolve/main/pytorch_model.bin
493 MB
- Xet hash:
- d050a3446bdc17ba8fa8b8ad53e0b8afc56a0b2f4f3efcc356ddf85fd455ad04
- Size of remote file:
- 493 MB
- SHA256:
- b37453b91c060ff243e7c7203bda7814639d8f08513b43b2a569e8adbc4d4d8a
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