Instructions to use YiYiXu/tiny-random-mclip-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YiYiXu/tiny-random-mclip-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="YiYiXu/tiny-random-mclip-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("YiYiXu/tiny-random-mclip-base") model = AutoModelForMaskedLM.from_pretrained("YiYiXu/tiny-random-mclip-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from YiYiXu/tiny-random-mclip-base: direct link, hf CLI and curl.
- Browser
- Download file 372 kB
-
https://huggingface.co/YiYiXu/tiny-random-mclip-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://YiYiXu/tiny-random-mclip-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/YiYiXu/tiny-random-mclip-base/resolve/main/pytorch_model.bin
372 kB
- Xet hash:
- 1637edb1eaf12cb230784f883057229df26f9c85caf3d38eef630591bc97bef0
- Size of remote file:
- 372 kB
- SHA256:
- b2ee837c5592061f1185cf652363f7b40569d46dafb05e60320cac9d5b3773a3
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