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
Upload model
Browse files- modeling_gzipembed.py +1 -1
modeling_gzipembed.py
CHANGED
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@@ -16,7 +16,7 @@ class GZIPEmbeddingModel(PreTrainedModel):
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self.reduction_head = None
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self.dummy_parameter = torch.nn.Parameter(torch.ones(1))
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def forward(self, prompt, num_procs=16):
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global calculate_ncd_row
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global p
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def calculate_ncd_row(data_row):
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self.reduction_head = None
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self.dummy_parameter = torch.nn.Parameter(torch.ones(1))
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def forward(self, prompt, num_procs=16, return_tensor=True):
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global calculate_ncd_row
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global p
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def calculate_ncd_row(data_row):
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