commit 3c72fa45d2ef60b7755cbbf4374403dfc4c20816 Author: ModelHub XC Date: Tue Jul 7 05:46:17 2026 +0800 初始化项目，由ModelHub XC社区提供模型 Model: RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf Source: Original Platform diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..227ee16 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,57 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs 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+e5-R-mistral-7b.IQ3_XS.gguf filter=lfs diff=lfs merge=lfs -text +e5-R-mistral-7b.IQ3_S.gguf filter=lfs diff=lfs merge=lfs -text +e5-R-mistral-7b.Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text +e5-R-mistral-7b.IQ3_M.gguf filter=lfs diff=lfs merge=lfs -text +e5-R-mistral-7b.Q3_K.gguf filter=lfs diff=lfs merge=lfs -text +e5-R-mistral-7b.Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text +e5-R-mistral-7b.Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text +e5-R-mistral-7b.IQ4_XS.gguf filter=lfs diff=lfs merge=lfs -text +e5-R-mistral-7b.Q4_0.gguf filter=lfs diff=lfs merge=lfs -text +e5-R-mistral-7b.IQ4_NL.gguf filter=lfs diff=lfs merge=lfs -text +e5-R-mistral-7b.Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text +e5-R-mistral-7b.Q4_K.gguf filter=lfs diff=lfs merge=lfs -text +e5-R-mistral-7b.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text +e5-R-mistral-7b.Q4_1.gguf filter=lfs diff=lfs merge=lfs -text +e5-R-mistral-7b.Q5_0.gguf filter=lfs diff=lfs merge=lfs -text +e5-R-mistral-7b.Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text +e5-R-mistral-7b.Q5_K.gguf filter=lfs diff=lfs merge=lfs -text +e5-R-mistral-7b.Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text +e5-R-mistral-7b.Q5_1.gguf filter=lfs diff=lfs merge=lfs -text +e5-R-mistral-7b.Q6_K.gguf filter=lfs diff=lfs merge=lfs -text +e5-R-mistral-7b.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..8cbc1ce --- /dev/null +++ b/README.md @@ -0,0 +1,1136 @@ +Quantization made by Richard Erkhov. + +[Github](https://github.com/RichardErkhov) + +[Discord](https://discord.gg/pvy7H8DZMG) + +[Request more models](https://github.com/RichardErkhov/quant_request) + + +e5-R-mistral-7b - GGUF +- Model creator: https://huggingface.co/BeastyZ/ +- Original model: https://huggingface.co/BeastyZ/e5-R-mistral-7b/ + + +| Name | Quant method | Size | +| ---- | ---- | ---- | +| [e5-R-mistral-7b.Q2_K.gguf](https://huggingface.co/RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf/blob/main/e5-R-mistral-7b.Q2_K.gguf) | Q2_K | 2.53GB | +| [e5-R-mistral-7b.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf/blob/main/e5-R-mistral-7b.IQ3_XS.gguf) | IQ3_XS | 2.81GB | +| [e5-R-mistral-7b.IQ3_S.gguf](https://huggingface.co/RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf/blob/main/e5-R-mistral-7b.IQ3_S.gguf) | IQ3_S | 2.96GB | +| [e5-R-mistral-7b.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf/blob/main/e5-R-mistral-7b.Q3_K_S.gguf) | Q3_K_S | 2.95GB | +| [e5-R-mistral-7b.IQ3_M.gguf](https://huggingface.co/RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf/blob/main/e5-R-mistral-7b.IQ3_M.gguf) | IQ3_M | 3.06GB | +| [e5-R-mistral-7b.Q3_K.gguf](https://huggingface.co/RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf/blob/main/e5-R-mistral-7b.Q3_K.gguf) | Q3_K | 3.28GB | +| [e5-R-mistral-7b.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf/blob/main/e5-R-mistral-7b.Q3_K_M.gguf) | Q3_K_M | 3.28GB | +| [e5-R-mistral-7b.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf/blob/main/e5-R-mistral-7b.Q3_K_L.gguf) | Q3_K_L | 3.56GB | +| [e5-R-mistral-7b.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf/blob/main/e5-R-mistral-7b.IQ4_XS.gguf) | IQ4_XS | 3.67GB | +| [e5-R-mistral-7b.Q4_0.gguf](https://huggingface.co/RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf/blob/main/e5-R-mistral-7b.Q4_0.gguf) | Q4_0 | 3.83GB | +| [e5-R-mistral-7b.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf/blob/main/e5-R-mistral-7b.IQ4_NL.gguf) | IQ4_NL | 3.87GB | +| [e5-R-mistral-7b.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf/blob/main/e5-R-mistral-7b.Q4_K_S.gguf) | Q4_K_S | 3.86GB | +| [e5-R-mistral-7b.Q4_K.gguf](https://huggingface.co/RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf/blob/main/e5-R-mistral-7b.Q4_K.gguf) | Q4_K | 4.07GB | +| [e5-R-mistral-7b.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf/blob/main/e5-R-mistral-7b.Q4_K_M.gguf) | Q4_K_M | 4.07GB | +| [e5-R-mistral-7b.Q4_1.gguf](https://huggingface.co/RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf/blob/main/e5-R-mistral-7b.Q4_1.gguf) | Q4_1 | 4.24GB | +| [e5-R-mistral-7b.Q5_0.gguf](https://huggingface.co/RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf/blob/main/e5-R-mistral-7b.Q5_0.gguf) | Q5_0 | 4.65GB | +| [e5-R-mistral-7b.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf/blob/main/e5-R-mistral-7b.Q5_K_S.gguf) | Q5_K_S | 4.65GB | +| [e5-R-mistral-7b.Q5_K.gguf](https://huggingface.co/RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf/blob/main/e5-R-mistral-7b.Q5_K.gguf) | Q5_K | 4.78GB | +| [e5-R-mistral-7b.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf/blob/main/e5-R-mistral-7b.Q5_K_M.gguf) | Q5_K_M | 4.78GB | +| [e5-R-mistral-7b.Q5_1.gguf](https://huggingface.co/RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf/blob/main/e5-R-mistral-7b.Q5_1.gguf) | Q5_1 | 5.07GB | +| [e5-R-mistral-7b.Q6_K.gguf](https://huggingface.co/RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf/blob/main/e5-R-mistral-7b.Q6_K.gguf) | Q6_K | 5.53GB | +| [e5-R-mistral-7b.Q8_0.gguf](https://huggingface.co/RichardErkhov/BeastyZ_-_e5-R-mistral-7b-gguf/blob/main/e5-R-mistral-7b.Q8_0.gguf) | Q8_0 | 7.17GB | + + + + +Original model description: +--- +library_name: transformers +license: apache-2.0 +datasets: +- BeastyZ/E5-R +language: +- en +model-index: +- name: e5-R-mistral-7b + results: + - dataset: + config: default + name: MTEB ArguAna + revision: None + split: test + type: mteb/arguana + metrics: + - type: map_at_1 + value: 33.57 + - type: map_at_10 + value: 49.952000000000005 + - type: map_at_100 + value: 50.673 + - type: map_at_1000 + value: 50.674 + - type: map_at_3 + value: 44.915 + - type: map_at_5 + value: 47.876999999999995 + - type: mrr_at_1 + value: 34.211000000000006 + - type: mrr_at_10 + value: 50.19 + - type: mrr_at_100 + value: 50.905 + - type: mrr_at_1000 + value: 50.906 + - type: mrr_at_3 + value: 45.128 + - type: mrr_at_5 + value: 48.097 + - type: ndcg_at_1 + value: 33.57 + - type: ndcg_at_10 + value: 58.994 + - type: ndcg_at_100 + value: 61.806000000000004 + - type: ndcg_at_1000 + value: 61.824999999999996 + - type: ndcg_at_3 + value: 48.681000000000004 + - type: ndcg_at_5 + value: 54.001 + - type: precision_at_1 + value: 33.57 + - type: precision_at_10 + value: 8.784 + - type: precision_at_100 + value: 0.9950000000000001 + - type: precision_at_1000 + value: 0.1 + - type: precision_at_3 + value: 19.867 + - type: precision_at_5 + value: 14.495 + - type: recall_at_1 + value: 33.57 + - type: recall_at_10 + value: 87.83800000000001 + - type: recall_at_100 + value: 99.502 + - type: recall_at_1000 + value: 99.644 + - type: recall_at_3 + value: 59.602 + - type: recall_at_5 + value: 72.475 + - type: main_score + value: 58.994 + task: + type: Retrieval + - dataset: + config: default + name: MTEB CQADupstackRetrieval + revision: None + split: test + type: mteb/cqadupstack + metrics: + - type: map_at_1 + value: 24.75 + - type: map_at_10 + value: 34.025 + - type: map_at_100 + value: 35.126000000000005 + - type: map_at_1000 + value: 35.219 + - type: map_at_3 + value: 31.607000000000003 + - type: map_at_5 + value: 32.962 + - type: mrr_at_1 + value: 27.357 + - type: mrr_at_10 + value: 36.370999999999995 + - type: mrr_at_100 + value: 37.364000000000004 + - type: mrr_at_1000 + value: 37.423 + - type: mrr_at_3 + value: 34.288000000000004 + - type: mrr_at_5 + value: 35.434 + - type: ndcg_at_1 + value: 27.357 + - type: ndcg_at_10 + value: 46.593999999999997 + - type: ndcg_at_100 + value: 44.317 + - type: ndcg_at_1000 + value: 46.475 + - type: ndcg_at_3 + value: 34.473 + - type: ndcg_at_5 + value: 36.561 + - type: precision_at_1 + value: 27.357 + - type: precision_at_10 + value: 6.081 + - type: precision_at_100 + value: 0.9299999999999999 + - type: precision_at_1000 + value: 0.124 + - type: precision_at_3 + value: 14.911 + - type: precision_at_5 + value: 10.24 + - type: recall_at_1 + value: 24.75 + - type: recall_at_10 + value: 51.856 + - type: recall_at_100 + value: 76.44300000000001 + - type: recall_at_1000 + value: 92.078 + - type: recall_at_3 + value: 39.427 + - type: recall_at_5 + value: 44.639 + - type: main_score + value: 46.593999999999997 + task: + type: Retrieval + - dataset: + config: default + name: MTEB ClimateFEVER + revision: None + split: test + type: mteb/climate-fever + metrics: + - type: map_at_1 + value: 16.436 + - type: map_at_10 + value: 29.693 + - type: map_at_100 + value: 32.179 + - type: map_at_1000 + value: 32.353 + - type: map_at_3 + value: 24.556 + - type: map_at_5 + value: 27.105 + - type: mrr_at_1 + value: 37.524 + - type: mrr_at_10 + value: 51.475 + - type: mrr_at_100 + value: 52.107000000000006 + - type: mrr_at_1000 + value: 52.123 + - type: mrr_at_3 + value: 48.35 + - type: mrr_at_5 + value: 50.249 + - type: ndcg_at_1 + value: 37.524 + - type: ndcg_at_10 + value: 40.258 + - type: ndcg_at_100 + value: 48.364000000000004 + - type: ndcg_at_1000 + value: 51.031000000000006 + - type: ndcg_at_3 + value: 33.359 + - type: ndcg_at_5 + value: 35.573 + - type: precision_at_1 + value: 37.524 + - type: precision_at_10 + value: 12.886000000000001 + - type: precision_at_100 + value: 2.169 + - type: precision_at_1000 + value: 0.268 + - type: precision_at_3 + value: 25.624000000000002 + - type: precision_at_5 + value: 19.453 + - type: recall_at_1 + value: 16.436 + - type: recall_at_10 + value: 47.77 + - type: recall_at_100 + value: 74.762 + - type: recall_at_1000 + value: 89.316 + - type: recall_at_3 + value: 30.508000000000003 + - type: recall_at_5 + value: 37.346000000000004 + - type: main_score + value: 40.258 + task: + type: Retrieval + - dataset: + config: default + name: MTEB DBPedia + revision: None + split: test + type: mteb/dbpedia + metrics: + - type: map_at_1 + value: 10.147 + - type: map_at_10 + value: 24.631 + - type: map_at_100 + value: 35.657 + - type: map_at_1000 + value: 37.824999999999996 + - type: map_at_3 + value: 16.423 + - type: map_at_5 + value: 19.666 + - type: mrr_at_1 + value: 76.5 + - type: mrr_at_10 + value: 82.793 + - type: mrr_at_100 + value: 83.015 + - type: mrr_at_1000 + value: 83.021 + - type: mrr_at_3 + value: 81.75 + - type: mrr_at_5 + value: 82.375 + - type: ndcg_at_1 + value: 64.75 + - type: ndcg_at_10 + value: 51.031000000000006 + - type: ndcg_at_100 + value: 56.005 + - type: ndcg_at_1000 + value: 63.068000000000005 + - type: ndcg_at_3 + value: 54.571999999999996 + - type: ndcg_at_5 + value: 52.66499999999999 + - type: precision_at_1 + value: 76.5 + - type: precision_at_10 + value: 42.15 + - type: precision_at_100 + value: 13.22 + - type: precision_at_1000 + value: 2.5989999999999998 + - type: precision_at_3 + value: 58.416999999999994 + - type: precision_at_5 + value: 52.2 + - type: recall_at_1 + value: 10.147 + - type: recall_at_10 + value: 30.786 + - type: recall_at_100 + value: 62.873000000000005 + - type: recall_at_1000 + value: 85.358 + - type: recall_at_3 + value: 17.665 + - type: recall_at_5 + value: 22.088 + - type: main_score + value: 51.031000000000006 + task: + type: Retrieval + - dataset: + config: default + name: MTEB FEVER + revision: None + split: test + type: mteb/fever + metrics: + - type: map_at_1 + value: 78.52900000000001 + - type: map_at_10 + value: 87.24199999999999 + - type: map_at_100 + value: 87.446 + - type: map_at_1000 + value: 87.457 + - type: map_at_3 + value: 86.193 + - type: map_at_5 + value: 86.898 + - type: mrr_at_1 + value: 84.518 + - type: mrr_at_10 + value: 90.686 + - type: mrr_at_100 + value: 90.73 + - type: mrr_at_1000 + value: 90.731 + - type: mrr_at_3 + value: 90.227 + - type: mrr_at_5 + value: 90.575 + - type: ndcg_at_1 + value: 84.518 + - type: ndcg_at_10 + value: 90.324 + - type: ndcg_at_100 + value: 90.96300000000001 + - type: ndcg_at_1000 + value: 91.134 + - type: ndcg_at_3 + value: 88.937 + - type: ndcg_at_5 + value: 89.788 + - type: precision_at_1 + value: 84.518 + - type: precision_at_10 + value: 10.872 + - type: precision_at_100 + value: 1.1440000000000001 + - type: precision_at_1000 + value: 0.117 + - type: precision_at_3 + value: 34.108 + - type: precision_at_5 + value: 21.154999999999998 + - type: recall_at_1 + value: 78.52900000000001 + - type: recall_at_10 + value: 96.123 + - type: recall_at_100 + value: 98.503 + - type: recall_at_1000 + value: 99.518 + - type: recall_at_3 + value: 92.444 + - type: recall_at_5 + value: 94.609 + - type: main_score + value: 90.324 + task: + type: Retrieval + - dataset: + config: default + name: MTEB FiQA2018 + revision: None + split: test + type: mteb/fiqa + metrics: + - type: map_at_1 + value: 29.38 + - type: map_at_10 + value: 50.28 + - type: map_at_100 + value: 52.532999999999994 + - type: map_at_1000 + value: 52.641000000000005 + - type: map_at_3 + value: 43.556 + - type: map_at_5 + value: 47.617 + - type: mrr_at_1 + value: 56.79 + - type: mrr_at_10 + value: 65.666 + - type: mrr_at_100 + value: 66.211 + - type: mrr_at_1000 + value: 66.226 + - type: mrr_at_3 + value: 63.452 + - type: mrr_at_5 + value: 64.895 + - type: ndcg_at_1 + value: 56.79 + - type: ndcg_at_10 + value: 58.68 + - type: ndcg_at_100 + value: 65.22 + - type: ndcg_at_1000 + value: 66.645 + - type: ndcg_at_3 + value: 53.981 + - type: ndcg_at_5 + value: 55.95 + - type: precision_at_1 + value: 56.79 + - type: precision_at_10 + value: 16.311999999999998 + - type: precision_at_100 + value: 2.316 + - type: precision_at_1000 + value: 0.258 + - type: precision_at_3 + value: 36.214 + - type: precision_at_5 + value: 27.067999999999998 + - type: recall_at_1 + value: 29.38 + - type: recall_at_10 + value: 66.503 + - type: recall_at_100 + value: 89.885 + - type: recall_at_1000 + value: 97.954 + - type: recall_at_3 + value: 48.866 + - type: recall_at_5 + value: 57.60999999999999 + - type: main_score + value: 58.68 + task: + type: Retrieval + - dataset: + config: default + name: MTEB HotpotQA + revision: None + split: test + type: mteb/hotpotqa + metrics: + - type: map_at_1 + value: 42.134 + - type: map_at_10 + value: 73.412 + - type: map_at_100 + value: 74.144 + - type: map_at_1000 + value: 74.181 + - type: map_at_3 + value: 70.016 + - type: map_at_5 + value: 72.174 + - type: mrr_at_1 + value: 84.267 + - type: mrr_at_10 + value: 89.18599999999999 + - type: mrr_at_100 + value: 89.29599999999999 + - type: mrr_at_1000 + value: 89.298 + - type: mrr_at_3 + value: 88.616 + - type: mrr_at_5 + value: 88.957 + - type: ndcg_at_1 + value: 84.267 + - type: ndcg_at_10 + value: 80.164 + - type: ndcg_at_100 + value: 82.52199999999999 + - type: ndcg_at_1000 + value: 83.176 + - type: ndcg_at_3 + value: 75.616 + - type: ndcg_at_5 + value: 78.184 + - type: precision_at_1 + value: 84.267 + - type: precision_at_10 + value: 16.916 + - type: precision_at_100 + value: 1.872 + - type: precision_at_1000 + value: 0.196 + - type: precision_at_3 + value: 49.71 + - type: precision_at_5 + value: 31.854 + - type: recall_at_1 + value: 42.134 + - type: recall_at_10 + value: 84.578 + - type: recall_at_100 + value: 93.606 + - type: recall_at_1000 + value: 97.86 + - type: recall_at_3 + value: 74.564 + - type: recall_at_5 + value: 79.635 + - type: main_score + value: 80.164 + task: + type: Retrieval + - dataset: + config: default + name: MTEB MSMARCO + revision: None + split: dev + type: mteb/msmarco + metrics: + - type: map_at_1 + value: 22.276 + - type: map_at_10 + value: 35.493 + - type: map_at_100 + value: 36.656 + - type: map_at_1000 + value: 36.699 + - type: map_at_3 + value: 31.320999999999998 + - type: map_at_5 + value: 33.772999999999996 + - type: mrr_at_1 + value: 22.966 + - type: mrr_at_10 + value: 36.074 + - type: mrr_at_100 + value: 37.183 + - type: mrr_at_1000 + value: 37.219 + - type: mrr_at_3 + value: 31.984 + - type: mrr_at_5 + value: 34.419 + - type: ndcg_at_1 + value: 22.966 + - type: ndcg_at_10 + value: 42.895 + - type: ndcg_at_100 + value: 48.453 + - type: ndcg_at_1000 + value: 49.464999999999996 + - type: ndcg_at_3 + value: 34.410000000000004 + - type: ndcg_at_5 + value: 38.78 + - type: precision_at_1 + value: 22.966 + - type: precision_at_10 + value: 6.88 + - type: precision_at_100 + value: 0.966 + - type: precision_at_1000 + value: 0.105 + - type: precision_at_3 + value: 14.785 + - type: precision_at_5 + value: 11.074 + - type: recall_at_1 + value: 22.276 + - type: recall_at_10 + value: 65.756 + - type: recall_at_100 + value: 91.34100000000001 + - type: recall_at_1000 + value: 98.957 + - type: recall_at_3 + value: 42.67 + - type: recall_at_5 + value: 53.161 + - type: main_score + value: 42.895 + task: + type: Retrieval + - dataset: + config: default + name: MTEB NFCorpus + revision: None + split: test + type: mteb/nfcorpus + metrics: + - type: map_at_1 + value: 7.188999999999999 + - type: map_at_10 + value: 16.176 + - type: map_at_100 + value: 20.504 + - type: map_at_1000 + value: 22.203999999999997 + - type: map_at_3 + value: 11.766 + - type: map_at_5 + value: 13.655999999999999 + - type: mrr_at_1 + value: 55.418 + - type: mrr_at_10 + value: 62.791 + - type: mrr_at_100 + value: 63.339 + - type: mrr_at_1000 + value: 63.369 + - type: mrr_at_3 + value: 60.99099999999999 + - type: mrr_at_5 + value: 62.059 + - type: ndcg_at_1 + value: 53.715 + - type: ndcg_at_10 + value: 41.377 + - type: ndcg_at_100 + value: 37.999 + - type: ndcg_at_1000 + value: 46.726 + - type: ndcg_at_3 + value: 47.262 + - type: ndcg_at_5 + value: 44.708999999999996 + - type: precision_at_1 + value: 55.108000000000004 + - type: precision_at_10 + value: 30.154999999999998 + - type: precision_at_100 + value: 9.582 + - type: precision_at_1000 + value: 2.2720000000000002 + - type: precision_at_3 + value: 43.55 + - type: precision_at_5 + value: 38.204 + - type: recall_at_1 + value: 7.188999999999999 + - type: recall_at_10 + value: 20.655 + - type: recall_at_100 + value: 38.068000000000005 + - type: recall_at_1000 + value: 70.208 + - type: recall_at_3 + value: 12.601 + - type: recall_at_5 + value: 15.573999999999998 + - type: main_score + value: 41.377 + task: + type: Retrieval + - dataset: + config: default + name: MTEB NQ + revision: None + split: test + type: mteb/nq + metrics: + - type: map_at_1 + value: 46.017 + - type: map_at_10 + value: 62.910999999999994 + - type: map_at_100 + value: 63.526 + - type: map_at_1000 + value: 63.536 + - type: map_at_3 + value: 59.077999999999996 + - type: map_at_5 + value: 61.521 + - type: mrr_at_1 + value: 51.68000000000001 + - type: mrr_at_10 + value: 65.149 + - type: mrr_at_100 + value: 65.542 + - type: mrr_at_1000 + value: 65.55 + - type: mrr_at_3 + value: 62.49 + - type: mrr_at_5 + value: 64.178 + - type: ndcg_at_1 + value: 51.651 + - type: ndcg_at_10 + value: 69.83500000000001 + - type: ndcg_at_100 + value: 72.18 + - type: ndcg_at_1000 + value: 72.393 + - type: ndcg_at_3 + value: 63.168 + - type: ndcg_at_5 + value: 66.958 + - type: precision_at_1 + value: 51.651 + - type: precision_at_10 + value: 10.626 + - type: precision_at_100 + value: 1.195 + - type: precision_at_1000 + value: 0.121 + - type: precision_at_3 + value: 28.012999999999998 + - type: precision_at_5 + value: 19.09 + - type: recall_at_1 + value: 46.017 + - type: recall_at_10 + value: 88.345 + - type: recall_at_100 + value: 98.129 + - type: recall_at_1000 + value: 99.696 + - type: recall_at_3 + value: 71.531 + - type: recall_at_5 + value: 80.108 + - type: main_score + value: 69.83500000000001 + task: + type: Retrieval + - dataset: + config: default + name: MTEB QuoraRetrieval + revision: None + split: test + type: mteb/quora + metrics: + - type: map_at_1 + value: 72.473 + - type: map_at_10 + value: 86.72800000000001 + - type: map_at_100 + value: 87.323 + - type: map_at_1000 + value: 87.332 + - type: map_at_3 + value: 83.753 + - type: map_at_5 + value: 85.627 + - type: mrr_at_1 + value: 83.39 + - type: mrr_at_10 + value: 89.149 + - type: mrr_at_100 + value: 89.228 + - type: mrr_at_1000 + value: 89.229 + - type: mrr_at_3 + value: 88.335 + - type: mrr_at_5 + value: 88.895 + - type: ndcg_at_1 + value: 83.39 + - type: ndcg_at_10 + value: 90.109 + - type: ndcg_at_100 + value: 91.09 + - type: ndcg_at_1000 + value: 91.13900000000001 + - type: ndcg_at_3 + value: 87.483 + - type: ndcg_at_5 + value: 88.942 + - type: precision_at_1 + value: 83.39 + - type: precision_at_10 + value: 13.711 + - type: precision_at_100 + value: 1.549 + - type: precision_at_1000 + value: 0.157 + - type: precision_at_3 + value: 38.342999999999996 + - type: precision_at_5 + value: 25.188 + - type: recall_at_1 + value: 72.473 + - type: recall_at_10 + value: 96.57 + - type: recall_at_100 + value: 99.792 + - type: recall_at_1000 + value: 99.99900000000001 + - type: recall_at_3 + value: 88.979 + - type: recall_at_5 + value: 93.163 + - type: main_score + value: 90.109 + task: + type: Retrieval + - dataset: + config: default + name: MTEB SCIDOCS + revision: None + split: test + type: mteb/scidocs + metrics: + - type: map_at_1 + value: 4.598 + - type: map_at_10 + value: 11.405999999999999 + - type: map_at_100 + value: 13.447999999999999 + - type: map_at_1000 + value: 13.758999999999999 + - type: map_at_3 + value: 8.332 + - type: map_at_5 + value: 9.709 + - type: mrr_at_1 + value: 22.6 + - type: mrr_at_10 + value: 32.978 + - type: mrr_at_100 + value: 34.149 + - type: mrr_at_1000 + value: 34.213 + - type: mrr_at_3 + value: 29.7 + - type: mrr_at_5 + value: 31.485000000000003 + - type: ndcg_at_1 + value: 22.6 + - type: ndcg_at_10 + value: 19.259999999999998 + - type: ndcg_at_100 + value: 27.21 + - type: ndcg_at_1000 + value: 32.7 + - type: ndcg_at_3 + value: 18.445 + - type: ndcg_at_5 + value: 15.812000000000001 + - type: precision_at_1 + value: 22.6 + - type: precision_at_10 + value: 9.959999999999999 + - type: precision_at_100 + value: 2.139 + - type: precision_at_1000 + value: 0.345 + - type: precision_at_3 + value: 17.299999999999997 + - type: precision_at_5 + value: 13.719999999999999 + - type: recall_at_1 + value: 4.598 + - type: recall_at_10 + value: 20.186999999999998 + - type: recall_at_100 + value: 43.362 + - type: recall_at_1000 + value: 70.11800000000001 + - type: recall_at_3 + value: 10.543 + - type: recall_at_5 + value: 13.923 + - type: main_score + value: 19.259999999999998 + task: + type: Retrieval + - dataset: + config: default + name: MTEB SciFact + revision: None + split: test + type: mteb/scifact + metrics: + - type: map_at_1 + value: 65.467 + - type: map_at_10 + value: 74.935 + - type: map_at_100 + value: 75.395 + - type: map_at_1000 + value: 75.412 + - type: map_at_3 + value: 72.436 + - type: map_at_5 + value: 73.978 + - type: mrr_at_1 + value: 68.667 + - type: mrr_at_10 + value: 76.236 + - type: mrr_at_100 + value: 76.537 + - type: mrr_at_1000 + value: 76.55499999999999 + - type: mrr_at_3 + value: 74.722 + - type: mrr_at_5 + value: 75.639 + - type: ndcg_at_1 + value: 68.667 + - type: ndcg_at_10 + value: 78.92099999999999 + - type: ndcg_at_100 + value: 80.645 + - type: ndcg_at_1000 + value: 81.045 + - type: ndcg_at_3 + value: 75.19500000000001 + - type: ndcg_at_5 + value: 77.114 + - type: precision_at_1 + value: 68.667 + - type: precision_at_10 + value: 10.133000000000001 + - type: precision_at_100 + value: 1.0999999999999999 + - type: precision_at_1000 + value: 0.11299999999999999 + - type: precision_at_3 + value: 28.889 + - type: precision_at_5 + value: 18.8 + - type: recall_at_1 + value: 65.467 + - type: recall_at_10 + value: 89.517 + - type: recall_at_100 + value: 97 + - type: recall_at_1000 + value: 100 + - type: recall_at_3 + value: 79.72200000000001 + - type: recall_at_5 + value: 84.511 + - type: main_score + value: 78.92099999999999 + task: + type: Retrieval + - dataset: + config: default + name: MTEB TRECCOVID + revision: None + split: test + type: mteb/trec-covid + metrics: + - type: map_at_1 + value: 0.244 + - type: map_at_10 + value: 2.183 + - type: map_at_100 + value: 13.712 + - type: map_at_1000 + value: 33.147 + - type: map_at_3 + value: 0.7270000000000001 + - type: map_at_5 + value: 1.199 + - type: mrr_at_1 + value: 94 + - type: mrr_at_10 + value: 97 + - type: mrr_at_100 + value: 97 + - type: mrr_at_1000 + value: 97 + - type: mrr_at_3 + value: 97 + - type: mrr_at_5 + value: 97 + - type: ndcg_at_1 + value: 92 + - type: ndcg_at_10 + value: 84.399 + - type: ndcg_at_100 + value: 66.771 + - type: ndcg_at_1000 + value: 59.092 + - type: ndcg_at_3 + value: 89.173 + - type: ndcg_at_5 + value: 88.52600000000001 + - type: precision_at_1 + value: 94 + - type: precision_at_10 + value: 86.8 + - type: precision_at_100 + value: 68.24 + - type: precision_at_1000 + value: 26.003999999999998 + - type: precision_at_3 + value: 92.667 + - type: precision_at_5 + value: 92.4 + - type: recall_at_1 + value: 0.244 + - type: recall_at_10 + value: 2.302 + - type: recall_at_100 + value: 16.622 + - type: recall_at_1000 + value: 55.175 + - type: recall_at_3 + value: 0.748 + - type: recall_at_5 + value: 1.247 + - type: main_score + value: 84.399 + task: + type: Retrieval + - dataset: + config: default + name: MTEB Touche2020 + revision: None + split: test + type: mteb/touche2020 + metrics: + - type: map_at_1 + value: 2.707 + - type: map_at_10 + value: 10.917 + - type: map_at_100 + value: 16.308 + - type: map_at_1000 + value: 17.953 + - type: map_at_3 + value: 5.65 + - type: map_at_5 + value: 7.379 + - type: mrr_at_1 + value: 34.694 + - type: mrr_at_10 + value: 49.745 + - type: mrr_at_100 + value: 50.309000000000005 + - type: mrr_at_1000 + value: 50.32 + - type: mrr_at_3 + value: 44.897999999999996 + - type: mrr_at_5 + value: 48.061 + - type: ndcg_at_1 + value: 33.672999999999995 + - type: ndcg_at_10 + value: 26.894000000000002 + - type: ndcg_at_100 + value: 37.423 + - type: ndcg_at_1000 + value: 49.376999999999995 + - type: ndcg_at_3 + value: 30.456 + - type: ndcg_at_5 + value: 27.772000000000002 + - type: precision_at_1 + value: 34.694 + - type: precision_at_10 + value: 23.878 + - type: precision_at_100 + value: 7.489999999999999 + - type: precision_at_1000 + value: 1.555 + - type: precision_at_3 + value: 31.293 + - type: precision_at_5 + value: 26.939 + - type: recall_at_1 + value: 2.707 + - type: recall_at_10 + value: 18.104 + - type: recall_at_100 + value: 46.93 + - type: recall_at_1000 + value: 83.512 + - type: recall_at_3 + value: 6.622999999999999 + - type: recall_at_5 + value: 10.051 + - type: main_score + value: 26.894000000000002 + task: + type: Retrieval +tags: +- mteb +--- + +# Model Card for e5-R-mistral-7b + + + +## Model Description + + + +e5-R-mistral-7b is a LLM retriever fine-tuned from [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1). + +- **Model type:** CausalLM +- **Repository:** Welcome to our [GitHub](https://github.com/LeeSureman/E5-Retrieval-Reproduction) repository to obtain code +- **Training dataset:** Dataset used for fine-tuning e5-R-mistral-7b is available [here](https://huggingface.co/datasets/BeastyZ/E5-R). + diff --git a/e5-R-mistral-7b.IQ3_M.gguf b/e5-R-mistral-7b.IQ3_M.gguf new file mode 100644 index 0000000..35aa41a --- /dev/null +++ b/e5-R-mistral-7b.IQ3_M.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:716b6bb89121ebf57c405de43d3bd69fb552ae10fb64849e14bc0890ae189668 +size 3284891744 diff --git a/e5-R-mistral-7b.IQ3_S.gguf b/e5-R-mistral-7b.IQ3_S.gguf new file mode 100644 index 0000000..f7dedaf --- /dev/null +++ b/e5-R-mistral-7b.IQ3_S.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7522d0a690db8b109cdf5489259396a828a006e67d77542347082c2ba700b70d +size 3182393440 diff --git a/e5-R-mistral-7b.IQ3_XS.gguf b/e5-R-mistral-7b.IQ3_XS.gguf new file mode 100644 index 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