Instructions to use crumb/gzip-openhermes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use crumb/gzip-openhermes with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("crumb/gzip-openhermes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -12,7 +12,7 @@ It's so funny that the huggingface hub lets you do this
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the huggingface pretrained model saving api requires at least one parameter, which is set to "1" in this model. also multiprocessing is suuuper weird so make sure you dont have the variables "p" or "calculate_ncd_row" in your code anywhere..
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| model | parameters | embedding dimensions |
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| meta-llama/Llama-2-70b-hf | 70b | 8192 |
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| crumb/gent-openhermes-augmented | 1* | 242,831 |
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the huggingface pretrained model saving api requires at least one parameter, which is set to "1" in this model. also multiprocessing is suuuper weird so make sure you dont have the variables "p" or "calculate_ncd_row" in your code anywhere..
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