Instructions to use trapoom555/MiniCPM-2B-Text-Embedding-cft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use trapoom555/MiniCPM-2B-Text-Embedding-cft with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("trapoom555/MiniCPM-2B-Text-Embedding-cft", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): aa8ab46
modify readme
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README.md
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| Loss | InfoNCE |
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| Batch Size | 60 |
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| InfoNCE Temperature | 0.05 |
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| Learning Rate |
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| Warmup Steps | 100 |
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| Learning Rate Scheduler | CosineAnnealingLR |
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| LoRA Rank | 8 |
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| Loss | InfoNCE |
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| Batch Size | 60 |
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| InfoNCE Temperature | 0.05 |
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| Learning Rate | 5e-05 |
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| Warmup Steps | 100 |
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| Learning Rate Scheduler | CosineAnnealingLR |
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| LoRA Rank | 8 |
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