task666_mmmlu_answer_generation_astronomy
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README.md
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# Model Card for
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<!-- Provide a quick summary of what the model is/does. -->
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:**
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:**
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- **Language(s) (NLP):**
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- **License:**
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- **Finetuned from model [optional]:**
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### Model Sources [optional]
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- **Repository:**
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- **Paper [optional]:**
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- **Demo [optional]:** [More Information Needed]
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## Uses
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### Training Procedure
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language: en
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license: mit
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library_name: keras
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# Model Card for Mistral-7B-Instruct-v0.2-4b-r16-task666
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LoRA trained on task666_mmmlu_answer_generation_astronomy
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- **Developed by:** bruel
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** LoRA
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- **Language(s) (NLP):** en
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- **License:** mit
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- **Finetuned from model [optional]:** mistralai/Mistral-7B-Instruct-v0.2
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** https://github.com/bruel-gabrielsson
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- **Paper [optional]:** "Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead" (2024), Rickard Brüel Gabrielsson, Jiacheng Zhu, Onkar Bhardwaj, Leshem Choshen, Kristjan Greenewald, Mikhail Yurochkin and Justin Solomon
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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"task666_mmmlu_answer_generation_astronomy" sourced from https://github.com/allenai/natural-instructions
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### Training Procedure
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