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
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## Description
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This is a fine-tuned version of [MiniCPM-2B-dpo-bf16](https://huggingface.co/openbmb/MiniCPM-2B-dpo-bf16) to perform Text Embedding tasks. The model is fine-tuned using the Contrastive Fine-tuning and LoRA technique on NLI datasets.
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## Base Model
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## Description
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This is a fine-tuned version of [MiniCPM-2B-dpo-bf16](https://huggingface.co/openbmb/MiniCPM-2B-dpo-bf16) to perform Text Embedding tasks. The model is fine-tuned using the Contrastive Fine-tuning and LoRA technique on NLI datasets. The paper can be found [here](https://arxiv.org/abs/2408.00690).
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## Base Model
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