snorkelai/Snorkel-Mistral-PairRM-DPO-Dataset
Dataset: This is the data used for training Snorkel model We use ONLY the prompts from UltraFeedback; no external LLM responses used. Methodology: Generate 5 response variations for each prompt from a subset of 20,000 using the LLM - to start, we used Mistral-7B-Instruct-v0.2. Apply PairRM for response reranking. Update the LLM by applying Direct Preference Optimization (DPO) on the top (chosen) and bottom (rejected) responses. Use this LLM as the base model for… See the full description on the dataset page: https://huggingface.co/datasets/snorkelai/Snorkel-Mistral-PairRM-DPO-Dataset.
| Author / organization | snorkelai |
|---|---|
| License (as declared) | apache-2.0 |
| Downloads | 230 (as reported by Hugging Face) |
| Likes | 46 |
| Created | 22 January 2024 |
| Last updated at source | 23 January 2024 |
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Connected in the knowledge graph
- mradermacher/Snorkel-Mistral-PairRM-DPO-GGUFModel · used to train
- brittlewis12/Snorkel-Mistral-PairRM-DPO-GGUFModel · used to train
- asedmammad/Contextual_KTO_Mistral_PairRM-GGUFModel · used to train
- mradermacher/Snorkel-Mistral-PairRM-DPO-i1-GGUFModel · used to train
Recent changes
- 17 Oct 2026 Description: Dataset: This is the data used for training Snorkel model We use ONLY the prompts from UltraFeedback; no external LLM responses used. Methodology: Generate 5 response variations for each prompt from a subset of 20,000 using the LLM - to sta → Dataset: This is the data used for training Snorkel model We use ONLY the prompts from UltraFeedback; no external LLM responses used. Methodology: Generate 5 response variations for each prompt from a subset of 20,000 using the LLM - to sta
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