Instructions to use ashabrawy/gumar_aligned_msa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ashabrawy/gumar_aligned_msa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ashabrawy/gumar_aligned_msa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ashabrawy/gumar_aligned_msa") model = AutoModel.from_pretrained("ashabrawy/gumar_aligned_msa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from ashabrawy/gumar_aligned_msa: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/ashabrawy/gumar_aligned_msa/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://ashabrawy/gumar_aligned_msa@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/ashabrawy/gumar_aligned_msa/resolve/refs%2Fpr%2F1/model.safetensors
436 MB
- Xet hash:
- b29edc3549f8f760c48b0260463d09be27de5c376295b8208a11a8995b6d1096
- Size of remote file:
- 436 MB
- SHA256:
- 9eb2d462db39ff50569750dc19ac303edbf56da42e3dbd061fd87111dcaace23
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