Model Summary
This is a fork of the original GritLM model. The main difference between this fork and the original model is the name of the architecture used in the config file. The new name is chosen to make it easier to adopt this model in vLLM.
GritLM is a generative representational instruction tuned language model. It unifies text representation (embedding) and text generation into a single model achieving state-of-the-art performance on both types of tasks.
- Repository: ContextualAI/gritlm
- Paper: https://arxiv.org/abs/2402.09906
- Logs: https://wandb.ai/muennighoff/gritlm/runs/0uui712t/overview
- Script: https://github.com/ContextualAI/gritlm/blob/main/scripts/training/train_gritlm_7b.sh
Model | Description |
---|---|
GritLM 7B | Mistral 7B finetuned using GRIT |
GritLM 8x7B | Mixtral 8x7B finetuned using GRIT |
Use
The model usage is documented here.
Citation
@misc{muennighoff2024generative,
title={Generative Representational Instruction Tuning},
author={Niklas Muennighoff and Hongjin Su and Liang Wang and Nan Yang and Furu Wei and Tao Yu and Amanpreet Singh and Douwe Kiela},
year={2024},
eprint={2402.09906},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
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Dataset used to train parasail-ai/GritLM-7B-vllm
Evaluation results
- accuracy on MTEB AmazonCounterfactualClassification (en)test set self-reported81.179
- ap on MTEB AmazonCounterfactualClassification (en)test set self-reported46.263
- f1 on MTEB AmazonCounterfactualClassification (en)test set self-reported75.446
- accuracy on MTEB AmazonPolarityClassificationtest set self-reported96.516
- ap on MTEB AmazonPolarityClassificationtest set self-reported94.791
- f1 on MTEB AmazonPolarityClassificationtest set self-reported96.515
- accuracy on MTEB AmazonReviewsClassification (en)test set self-reported57.806
- f1 on MTEB AmazonReviewsClassification (en)test set self-reported56.784
- map_at_1 on MTEB ArguAnatest set self-reported38.478
- map_at_10 on MTEB ArguAnatest set self-reported54.955