Instructions to use hf-tiny-model-private/tiny-random-PerceiverForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-PerceiverForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-tiny-model-private/tiny-random-PerceiverForMaskedLM")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-PerceiverForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-tiny-model-private/tiny-random-PerceiverForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-PerceiverForMaskedLM: direct link, hf CLI and curl.
- Browser
- Download file 9.22 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-PerceiverForMaskedLM/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-PerceiverForMaskedLM@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-PerceiverForMaskedLM/resolve/refs%2Fpr%2F1/model.safetensors
9.22 MB
- Xet hash:
- 24f186279faee30c694f8581575590a2b198cc40693a772ddd8a0559416be48a
- Size of remote file:
- 9.22 MB
- SHA256:
- f45eed5a3b6e9deb7bda43e8e79493178a53ded8d38cf27f56aaaa279ce67991
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