|
--- |
|
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-Q4_K_M-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-Q4_K_M-GGUF --hf-file chuxin-embedding-q4_k_m.gguf -p "The meaning to life and the universe is" |
|
``` |
|
|
|
### Server: |
|
```bash |
|
llama-server --hf-repo lagoon999/Chuxin-Embedding-Q4_K_M-GGUF --hf-file chuxin-embedding-q4_k_m.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 |
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``` |
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|
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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). |
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``` |
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cd llama.cpp && LLAMA_CURL=1 make |
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``` |
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|
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Step 3: Run inference through the main binary. |
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``` |
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./llama-cli --hf-repo lagoon999/Chuxin-Embedding-Q4_K_M-GGUF --hf-file chuxin-embedding-q4_k_m.gguf -p "The meaning to life and the universe is" |
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``` |
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or |
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``` |
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./llama-server --hf-repo lagoon999/Chuxin-Embedding-Q4_K_M-GGUF --hf-file chuxin-embedding-q4_k_m.gguf -c 2048 |
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``` |
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|
