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--- |
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base_model: intfloat/e5-mistral-7b-instruct |
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license: mit |
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model_creator: intfloat |
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quantized_by: Second State Inc. |
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language: en |
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--- |
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<div style="width: auto; margin-left: auto; margin-right: auto"> |
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<img src="https://github.com/LlamaEdge/LlamaEdge/raw/dev/assets/logo.svg" style="width: 100%; min-width: 400px; display: block; margin: auto;"> |
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</div> |
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<hr style="margin-top: 1.0em; margin-bottom: 1.0em;"> |
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<!-- header end --> |
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# E5-Mistral-7B-Instruct-Embedding-GGUF |
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## Original Model |
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[intfloat/e5-mistral-7b-instruct](https://huggingface.co/intfloat/e5-mistral-7b-instruct) |
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## Run with LlamaEdge |
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- LlamaEdge version: [v0.8.2](https://github.com/LlamaEdge/LlamaEdge/releases/tag/0.8.2) and above |
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- Prompt template |
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- Prompt type: `embedding` |
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- Context size: `4096` |
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- Run as LlamaEdge service |
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```bash |
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wasmedge --dir .:. --nn-preload default:GGML:AUTO:e5-mistral-7b-instruct-Q5_K_M.gguf \ |
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llama-api-server.wasm \ |
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--prompt-template embedding \ |
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--ctx-size 4096 \ |
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--model-name e5-mistral-7b-instruct |
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``` |
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## Quantized GGUF Models |
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| Name | Quant method | Bits | Size | Use case | |
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| ---- | ---- | ---- | ---- | ----- | |
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| [e5-mistral-7b-instruct-Q2_K.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q2_K.gguf) | Q2_K | 2 | 2.72 GB| smallest, significant quality loss - not recommended for most purposes | |
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| [e5-mistral-7b-instruct-Q3_K_L.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q3_K_L.gguf) | Q3_K_L | 3 | 3.82 GB| small, substantial quality loss | |
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| [e5-mistral-7b-instruct-Q3_K_M.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q3_K_M.gguf) | Q3_K_M | 3 | 3.52 GB| very small, high quality loss | |
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| [e5-mistral-7b-instruct-Q3_K_S.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q3_K_S.gguf) | Q3_K_S | 3 | 3.16 GB| very small, high quality loss | |
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| [e5-mistral-7b-instruct-Q4_0.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q4_0.gguf) | Q4_0 | 4 | 4.11 GB| legacy; small, very high quality loss - prefer using Q3_K_M | |
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| [e5-mistral-7b-instruct-Q4_K_M.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q4_K_M.gguf) | Q4_K_M | 4 | 4.37 GB| medium, balanced quality - recommended | |
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| [e5-mistral-7b-instruct-Q4_K_S.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q4_K_S.gguf) | Q4_K_S | 4 | 4.14 GB| small, greater quality loss | |
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| [e5-mistral-7b-instruct-Q5_0.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q5_0.gguf) | Q5_0 | 5 | 5.00 GB| legacy; medium, balanced quality - prefer using Q4_K_M | |
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| [e5-mistral-7b-instruct-Q5_K_M.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q5_K_M.gguf) | Q5_K_M | 5 | 5.13 GB| large, very low quality loss - recommended | |
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| [e5-mistral-7b-instruct-Q5_K_S.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q5_K_S.gguf) | Q5_K_S | 5 | 5.00 GB| large, low quality loss - recommended | |
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| [e5-mistral-7b-instruct-Q6_K.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q6_K.gguf) | Q6_K | 6 | 5.94 GB| very large, extremely low quality loss | |
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| [e5-mistral-7b-instruct-Q8_0.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q8_0.gguf) | Q8_0 | 8 | 7.7 GB| very large, extremely low quality loss - not recommended | |
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| [e5-mistral-7b-instruct-f16.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-f16.gguf) | f16 | 8 | 14.5 GB| very large, extremely low quality loss - not recommended | |
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*Quantized with llama.cpp b2334* |
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