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README.md

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+---
+language:
+- zh
+tags:
+- mteb
+- llama-cpp
+- gguf-my-repo
+base_model: chuxin-llm/Chuxin-Embedding
+model-index:
+- name: Chuxin-Embedding
+  results:
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CmedqaRetrieval (default)
+      type: C-MTEB/CmedqaRetrieval
+      config: default
+      split: dev
+      revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
+    metrics:
+    - type: map_at_1
+      value: 33.391999999999996
+    - type: map_at_10
+      value: 48.715
+    - type: map_at_100
+      value: 50.381
+    - type: map_at_1000
+      value: 50.456
+    - type: map_at_3
+      value: 43.708999999999996
+    - type: map_at_5
+      value: 46.405
+    - type: mrr_at_1
+      value: 48.612
+    - type: mrr_at_10
+      value: 58.67099999999999
+    - type: mrr_at_100
+      value: 59.38
+    - type: mrr_at_1000
+      value: 59.396
+    - type: mrr_at_3
+      value: 55.906
+    - type: mrr_at_5
+      value: 57.421
+    - type: ndcg_at_1
+      value: 48.612
+    - type: ndcg_at_10
+      value: 56.581
+    - type: ndcg_at_100
+      value: 62.422999999999995
+    - type: ndcg_at_1000
+      value: 63.476
+    - type: ndcg_at_3
+      value: 50.271
+    - type: ndcg_at_5
+      value: 52.79899999999999
+    - type: precision_at_1
+      value: 48.612
+    - type: precision_at_10
+      value: 11.995000000000001
+    - type: precision_at_100
+      value: 1.696
+    - type: precision_at_1000
+      value: 0.185
+    - type: precision_at_3
+      value: 27.465
+    - type: precision_at_5
+      value: 19.675
+    - type: recall_at_1
+      value: 33.391999999999996
+    - type: recall_at_10
+      value: 69.87100000000001
+    - type: recall_at_100
+      value: 93.078
+    - type: recall_at_1000
+      value: 99.55199999999999
+    - type: recall_at_3
+      value: 50.939
+    - type: recall_at_5
+      value: 58.714
+    - type: main_score
+      value: 56.581
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CovidRetrieval (default)
+      type: C-MTEB/CovidRetrieval
+      config: default
+      split: dev
+      revision: 1271c7809071a13532e05f25fb53511ffce77117
+    metrics:
+    - type: map_at_1
+      value: 71.918
+    - type: map_at_10
+      value: 80.609
+    - type: map_at_100
+      value: 80.796
+    - type: map_at_1000
+      value: 80.798
+    - type: map_at_3
+      value: 79.224
+    - type: map_at_5
+      value: 79.96
+    - type: mrr_at_1
+      value: 72.076
+    - type: mrr_at_10
+      value: 80.61399999999999
+    - type: mrr_at_100
+      value: 80.801
+    - type: mrr_at_1000
+      value: 80.803
+    - type: mrr_at_3
+      value: 79.276
+    - type: mrr_at_5
+      value: 80.025
+    - type: ndcg_at_1
+      value: 72.076
+    - type: ndcg_at_10
+      value: 84.286
+    - type: ndcg_at_100
+      value: 85.14500000000001
+    - type: ndcg_at_1000
+      value: 85.21
+    - type: ndcg_at_3
+      value: 81.45400000000001
+    - type: ndcg_at_5
+      value: 82.781
+    - type: precision_at_1
+      value: 72.076
+    - type: precision_at_10
+      value: 9.663
+    - type: precision_at_100
+      value: 1.005
+    - type: precision_at_1000
+      value: 0.101
+    - type: precision_at_3
+      value: 29.398999999999997
+    - type: precision_at_5
+      value: 18.335
+    - type: recall_at_1
+      value: 71.918
+    - type: recall_at_10
+      value: 95.574
+    - type: recall_at_100
+      value: 99.473
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_3
+      value: 87.82900000000001
+    - type: recall_at_5
+      value: 90.991
+    - type: main_score
+      value: 84.286
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB DuRetrieval (default)
+      type: C-MTEB/DuRetrieval
+      config: default
+      split: dev
+      revision: a1a333e290fe30b10f3f56498e3a0d911a693ced
+    metrics:
+    - type: map_at_1
+      value: 25.019999999999996
+    - type: map_at_10
+      value: 77.744
+    - type: map_at_100
+      value: 80.562
+    - type: map_at_1000
+      value: 80.60300000000001
+    - type: map_at_3
+      value: 52.642999999999994
+    - type: map_at_5
+      value: 67.179
+    - type: mrr_at_1
+      value: 86.5
+    - type: mrr_at_10
+      value: 91.024
+    - type: mrr_at_100
+      value: 91.09
+    - type: mrr_at_1000
+      value: 91.093
+    - type: mrr_at_3
+      value: 90.558
+    - type: mrr_at_5
+      value: 90.913
+    - type: ndcg_at_1
+      value: 86.5
+    - type: ndcg_at_10
+      value: 85.651
+    - type: ndcg_at_100
+      value: 88.504
+    - type: ndcg_at_1000
+      value: 88.887
+    - type: ndcg_at_3
+      value: 82.707
+    - type: ndcg_at_5
+      value: 82.596
+    - type: precision_at_1
+      value: 86.5
+    - type: precision_at_10
+      value: 41.595
+    - type: precision_at_100
+      value: 4.7940000000000005
+    - type: precision_at_1000
+      value: 0.48900000000000005
+    - type: precision_at_3
+      value: 74.233
+    - type: precision_at_5
+      value: 63.68000000000001
+    - type: recall_at_1
+      value: 25.019999999999996
+    - type: recall_at_10
+      value: 88.114
+    - type: recall_at_100
+      value: 97.442
+    - type: recall_at_1000
+      value: 99.39099999999999
+    - type: recall_at_3
+      value: 55.397
+    - type: recall_at_5
+      value: 73.095
+    - type: main_score
+      value: 85.651
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB EcomRetrieval (default)
+      type: C-MTEB/EcomRetrieval
+      config: default
+      split: dev
+      revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9
+    metrics:
+    - type: map_at_1
+      value: 55.60000000000001
+    - type: map_at_10
+      value: 67.891
+    - type: map_at_100
+      value: 68.28699999999999
+    - type: map_at_1000
+      value: 68.28699999999999
+    - type: map_at_3
+      value: 64.86699999999999
+    - type: map_at_5
+      value: 66.652
+    - type: mrr_at_1
+      value: 55.60000000000001
+    - type: mrr_at_10
+      value: 67.891
+    - type: mrr_at_100
+      value: 68.28699999999999
+    - type: mrr_at_1000
+      value: 68.28699999999999
+    - type: mrr_at_3
+      value: 64.86699999999999
+    - type: mrr_at_5
+      value: 66.652
+    - type: ndcg_at_1
+      value: 55.60000000000001
+    - type: ndcg_at_10
+      value: 74.01100000000001
+    - type: ndcg_at_100
+      value: 75.602
+    - type: ndcg_at_1000
+      value: 75.602
+    - type: ndcg_at_3
+      value: 67.833
+    - type: ndcg_at_5
+      value: 71.005
+    - type: precision_at_1
+      value: 55.60000000000001
+    - type: precision_at_10
+      value: 9.33
+    - type: precision_at_100
+      value: 1.0
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 25.467000000000002
+    - type: precision_at_5
+      value: 16.8
+    - type: recall_at_1
+      value: 55.60000000000001
+    - type: recall_at_10
+      value: 93.30000000000001
+    - type: recall_at_100
+      value: 100.0
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_3
+      value: 76.4
+    - type: recall_at_5
+      value: 84.0
+    - type: main_score
+      value: 74.01100000000001
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB MMarcoRetrieval (default)
+      type: C-MTEB/MMarcoRetrieval
+      config: default
+      split: dev
+      revision: 539bbde593d947e2a124ba72651aafc09eb33fc2
+    metrics:
+    - type: map_at_1
+      value: 66.24799999999999
+    - type: map_at_10
+      value: 75.356
+    - type: map_at_100
+      value: 75.653
+    - type: map_at_1000
+      value: 75.664
+    - type: map_at_3
+      value: 73.515
+    - type: map_at_5
+      value: 74.67099999999999
+    - type: mrr_at_1
+      value: 68.496
+    - type: mrr_at_10
+      value: 75.91499999999999
+    - type: mrr_at_100
+      value: 76.17399999999999
+    - type: mrr_at_1000
+      value: 76.184
+    - type: mrr_at_3
+      value: 74.315
+    - type: mrr_at_5
+      value: 75.313
+    - type: ndcg_at_1
+      value: 68.496
+    - type: ndcg_at_10
+      value: 79.065
+    - type: ndcg_at_100
+      value: 80.417
+    - type: ndcg_at_1000
+      value: 80.72399999999999
+    - type: ndcg_at_3
+      value: 75.551
+    - type: ndcg_at_5
+      value: 77.505
+    - type: precision_at_1
+      value: 68.496
+    - type: precision_at_10
+      value: 9.563
+    - type: precision_at_100
+      value: 1.024
+    - type: precision_at_1000
+      value: 0.105
+    - type: precision_at_3
+      value: 28.391
+    - type: precision_at_5
+      value: 18.086
+    - type: recall_at_1
+      value: 66.24799999999999
+    - type: recall_at_10
+      value: 89.97
+    - type: recall_at_100
+      value: 96.13199999999999
+    - type: recall_at_1000
+      value: 98.551
+    - type: recall_at_3
+      value: 80.624
+    - type: recall_at_5
+      value: 85.271
+    - type: main_score
+      value: 79.065
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB MedicalRetrieval (default)
+      type: C-MTEB/MedicalRetrieval
+      config: default
+      split: dev
+      revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6
+    metrics:
+    - type: map_at_1
+      value: 61.8
+    - type: map_at_10
+      value: 71.101
+    - type: map_at_100
+      value: 71.576
+    - type: map_at_1000
+      value: 71.583
+    - type: map_at_3
+      value: 68.867
+    - type: map_at_5
+      value: 70.272
+    - type: mrr_at_1
+      value: 61.9
+    - type: mrr_at_10
+      value: 71.158
+    - type: mrr_at_100
+      value: 71.625
+    - type: mrr_at_1000
+      value: 71.631
+    - type: mrr_at_3
+      value: 68.917
+    - type: mrr_at_5
+      value: 70.317
+    - type: ndcg_at_1
+      value: 61.8
+    - type: ndcg_at_10
+      value: 75.624
+    - type: ndcg_at_100
+      value: 77.702
+    - type: ndcg_at_1000
+      value: 77.836
+    - type: ndcg_at_3
+      value: 71.114
+    - type: ndcg_at_5
+      value: 73.636
+    - type: precision_at_1
+      value: 61.8
+    - type: precision_at_10
+      value: 8.98
+    - type: precision_at_100
+      value: 0.9900000000000001
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 25.867
+    - type: precision_at_5
+      value: 16.74
+    - type: recall_at_1
+      value: 61.8
+    - type: recall_at_10
+      value: 89.8
+    - type: recall_at_100
+      value: 99.0
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_3
+      value: 77.60000000000001
+    - type: recall_at_5
+      value: 83.7
+    - type: main_score
+      value: 75.624
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB T2Retrieval (default)
+      type: C-MTEB/T2Retrieval
+      config: default
+      split: dev
+      revision: 8731a845f1bf500a4f111cf1070785c793d10e64
+    metrics:
+    - type: map_at_1
+      value: 27.173000000000002
+    - type: map_at_10
+      value: 76.454
+    - type: map_at_100
+      value: 80.021
+    - type: map_at_1000
+      value: 80.092
+    - type: map_at_3
+      value: 53.876999999999995
+    - type: map_at_5
+      value: 66.122
+    - type: mrr_at_1
+      value: 89.519
+    - type: mrr_at_10
+      value: 92.091
+    - type: mrr_at_100
+      value: 92.179
+    - type: mrr_at_1000
+      value: 92.183
+    - type: mrr_at_3
+      value: 91.655
+    - type: mrr_at_5
+      value: 91.94
+    - type: ndcg_at_1
+      value: 89.519
+    - type: ndcg_at_10
+      value: 84.043
+    - type: ndcg_at_100
+      value: 87.60900000000001
+    - type: ndcg_at_1000
+      value: 88.32799999999999
+    - type: ndcg_at_3
+      value: 85.623
+    - type: ndcg_at_5
+      value: 84.111
+    - type: precision_at_1
+      value: 89.519
+    - type: precision_at_10
+      value: 41.760000000000005
+    - type: precision_at_100
+      value: 4.982
+    - type: precision_at_1000
+      value: 0.515
+    - type: precision_at_3
+      value: 74.944
+    - type: precision_at_5
+      value: 62.705999999999996
+    - type: recall_at_1
+      value: 27.173000000000002
+    - type: recall_at_10
+      value: 82.878
+    - type: recall_at_100
+      value: 94.527
+    - type: recall_at_1000
+      value: 98.24199999999999
+    - type: recall_at_3
+      value: 55.589
+    - type: recall_at_5
+      value: 69.476
+    - type: main_score
+      value: 84.043
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB VideoRetrieval (default)
+      type: C-MTEB/VideoRetrieval
+      config: default
+      split: dev
+      revision: 58c2597a5943a2ba48f4668c3b90d796283c5639
+    metrics:
+    - type: map_at_1
+      value: 70.1
+    - type: map_at_10
+      value: 79.62
+    - type: map_at_100
+      value: 79.804
+    - type: map_at_1000
+      value: 79.804
+    - type: map_at_3
+      value: 77.81700000000001
+    - type: map_at_5
+      value: 79.037
+    - type: mrr_at_1
+      value: 70.1
+    - type: mrr_at_10
+      value: 79.62
+    - type: mrr_at_100
+      value: 79.804
+    - type: mrr_at_1000
+      value: 79.804
+    - type: mrr_at_3
+      value: 77.81700000000001
+    - type: mrr_at_5
+      value: 79.037
+    - type: ndcg_at_1
+      value: 70.1
+    - type: ndcg_at_10
+      value: 83.83500000000001
+    - type: ndcg_at_100
+      value: 84.584
+    - type: ndcg_at_1000
+      value: 84.584
+    - type: ndcg_at_3
+      value: 80.282
+    - type: ndcg_at_5
+      value: 82.472
+    - type: precision_at_1
+      value: 70.1
+    - type: precision_at_10
+      value: 9.68
+    - type: precision_at_100
+      value: 1.0
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 29.133
+    - type: precision_at_5
+      value: 18.54
+    - type: recall_at_1
+      value: 70.1
+    - type: recall_at_10
+      value: 96.8
+    - type: recall_at_100
+      value: 100.0
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_3
+      value: 87.4
+    - type: recall_at_5
+      value: 92.7
+    - type: main_score
+      value: 83.83500000000001
+---
+
+# lagoon999/Chuxin-Embedding-Q8_0-GGUF
+This model was converted to GGUF format from [`chuxin-llm/Chuxin-Embedding`](https://huggingface.co/chuxin-llm/Chuxin-Embedding) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
+Refer to the [original model card](https://huggingface.co/chuxin-llm/Chuxin-Embedding) for more details on the model.
+
+## Use with llama.cpp
+Install llama.cpp through brew (works on Mac and Linux)
+
+```bash
+brew install llama.cpp
+
+```
+Invoke the llama.cpp server or the CLI.
+
+### CLI:
+```bash
+llama-cli --hf-repo lagoon999/Chuxin-Embedding-Q8_0-GGUF --hf-file chuxin-embedding-q8_0.gguf -p "The meaning to life and the universe is"
+```
+
+### Server:
+```bash
+llama-server --hf-repo lagoon999/Chuxin-Embedding-Q8_0-GGUF --hf-file chuxin-embedding-q8_0.gguf -c 2048
+```
+
+Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
+
+Step 1: Clone llama.cpp from GitHub.
+```
+git clone https://github.com/ggerganov/llama.cpp
+```
+
+Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
+```
+cd llama.cpp && LLAMA_CURL=1 make
+```
+
+Step 3: Run inference through the main binary.
+```
+./llama-cli --hf-repo lagoon999/Chuxin-Embedding-Q8_0-GGUF --hf-file chuxin-embedding-q8_0.gguf -p "The meaning to life and the universe is"
+```
+or 
+```
+./llama-server --hf-repo lagoon999/Chuxin-Embedding-Q8_0-GGUF --hf-file chuxin-embedding-q8_0.gguf -c 2048
+```