Feature Extraction
Transformers
Safetensors
mists
time series
multimodal
TimeSeries-Text-to-Text
custom_code
Instructions to use HachiML/Mists-7B-v01-not-trained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HachiML/Mists-7B-v01-not-trained with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="HachiML/Mists-7B-v01-not-trained", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("HachiML/Mists-7B-v01-not-trained", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload processing_mists.py
Browse files- processing_mists.py +1 -1
processing_mists.py
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@@ -64,7 +64,7 @@ class MistsProcessor(ProcessorMixin):
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else:
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text_inputs = {"text": text}
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else:
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-
text_inputs =
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return BatchFeature(data={**text_inputs, **time_series_values})
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else:
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text_inputs = {"text": text}
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else:
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text_inputs = {}
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return BatchFeature(data={**text_inputs, **time_series_values})
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