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Alibaba-NLP/gte-Qwen2-7B-instruct - GGUF
This repo contains GGUF format model files for Alibaba-NLP/gte-Qwen2-7B-instruct.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.
Prompt template
<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
Model file specification
Filename | Quant type | File Size | Description |
---|---|---|---|
gte-Qwen2-7B-instruct-Q2_K.gguf | Q2_K | 2.807 GB | smallest, significant quality loss - not recommended for most purposes |
gte-Qwen2-7B-instruct-Q3_K_S.gguf | Q3_K_S | 3.251 GB | very small, high quality loss |
gte-Qwen2-7B-instruct-Q3_K_M.gguf | Q3_K_M | 3.545 GB | very small, high quality loss |
gte-Qwen2-7B-instruct-Q3_K_L.gguf | Q3_K_L | 3.806 GB | small, substantial quality loss |
gte-Qwen2-7B-instruct-Q4_0.gguf | Q4_0 | 4.125 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
gte-Qwen2-7B-instruct-Q4_K_S.gguf | Q4_K_S | 4.150 GB | small, greater quality loss |
gte-Qwen2-7B-instruct-Q4_K_M.gguf | Q4_K_M | 4.360 GB | medium, balanced quality - recommended |
gte-Qwen2-7B-instruct-Q5_0.gguf | Q5_0 | 4.948 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
gte-Qwen2-7B-instruct-Q5_K_S.gguf | Q5_K_S | 4.948 GB | large, low quality loss - recommended |
gte-Qwen2-7B-instruct-Q5_K_M.gguf | Q5_K_M | 5.069 GB | large, very low quality loss - recommended |
gte-Qwen2-7B-instruct-Q6_K.gguf | Q6_K | 5.822 GB | very large, extremely low quality loss |
gte-Qwen2-7B-instruct-Q8_0.gguf | Q8_0 | 7.539 GB | very large, extremely low quality loss - not recommended |
Downloading instruction
Command line
Firstly, install Huggingface Client
pip install -U "huggingface_hub[cli]"
Then, downoad the individual model file the a local directory
huggingface-cli download tensorblock/gte-Qwen2-7B-instruct-GGUF --include "gte-Qwen2-7B-instruct-Q2_K.gguf" --local-dir MY_LOCAL_DIR
If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf
), you can try:
huggingface-cli download tensorblock/gte-Qwen2-7B-instruct-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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Model tree for tensorblock/gte-Qwen2-7B-instruct-GGUF
Base model
Alibaba-NLP/gte-Qwen2-7B-instructEvaluation results
- accuracy on MTEB AmazonCounterfactualClassification (en)test set self-reported91.313
- ap on MTEB AmazonCounterfactualClassification (en)test set self-reported67.643
- f1 on MTEB AmazonCounterfactualClassification (en)test set self-reported87.534
- accuracy on MTEB AmazonPolarityClassificationtest set self-reported97.498
- ap on MTEB AmazonPolarityClassificationtest set self-reported96.303
- f1 on MTEB AmazonPolarityClassificationtest set self-reported97.498
- accuracy on MTEB AmazonReviewsClassification (en)test set self-reported62.564
- f1 on MTEB AmazonReviewsClassification (en)test set self-reported60.976
- map_at_1 on MTEB ArguAnatest set self-reported36.486
- map_at_10 on MTEB ArguAnatest set self-reported54.842