Instructions to use m-a-p/Kun-PrimaryChatModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m-a-p/Kun-PrimaryChatModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="m-a-p/Kun-PrimaryChatModel", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("m-a-p/Kun-PrimaryChatModel", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload all_results.json with huggingface_hub
Browse files- all_results.json +7 -0
all_results.json
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{
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"epoch": 4.96,
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"train_loss": 0.6916719505221259,
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"train_runtime": 14223.7593,
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"train_samples_per_second": 4.44,
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"train_steps_per_second": 0.034
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}
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