Instructions to use approach0/backbone-cotmae-600 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use approach0/backbone-cotmae-600 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="approach0/backbone-cotmae-600")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("approach0/backbone-cotmae-600") model = AutoModelForPreTraining.from_pretrained("approach0/backbone-cotmae-600", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download params.json from approach0/backbone-cotmae-600: direct link, hf CLI and curl.
- Browser
- Download file 16 Bytes
-
https://huggingface.co/approach0/backbone-cotmae-600/resolve/refs%2Fpr%2F1/params.json
- Command line
-
hf download hf://approach0/backbone-cotmae-600@refs/pr/1/params.json
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curl -L -o params.json https://huggingface.co/approach0/backbone-cotmae-600/resolve/refs%2Fpr%2F1/params.json
16 Bytes
| ["cotmae", 2, 6] |