Instructions to use KilmaAI/Sadim-77M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KilmaAI/Sadim-77M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="KilmaAI/Sadim-77M")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("KilmaAI/Sadim-77M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from KilmaAI/Sadim-77M: direct link, hf CLI and curl.
- Browser
- Download file 312 MB
-
https://huggingface.co/KilmaAI/Sadim-77M/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://KilmaAI/Sadim-77M/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/KilmaAI/Sadim-77M/resolve/main/pytorch_model.bin
312 MB
- Xet hash:
- 24831f6c3d49fda0f3c80431cf055beb6c2ac8dccc8560d068fee2605589a99e
- Size of remote file:
- 312 MB
- SHA256:
- c7e712bbcab4b555647bccf4d98d1f984b0a0bb7f1e6b1cdca0aaf3190384e9f
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