Instructions to use CompassioninMachineLearning/Pretrained_twentyK_cleanChat_split_with_instr_masking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CompassioninMachineLearning/Pretrained_twentyK_cleanChat_split_with_instr_masking with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("CompassioninMachineLearning/Pretrained_twentyK_cleanChat_split_with_instr_masking", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a22be11de2ab17fd158a5702b8fdd7922a9d2cdd180cf48ab35a5a11ac0df35
- Size of remote file:
- 54.6 MB
- SHA256:
- 2670da8e7e69e5c0c8889c00a9d30d5a3858a63c64d1026dd23975a404814b33
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