metadata

base_model: mistralai/Mistral-7B-Instruct-v0.1
inference: false
license: apache-2.0
model_creator: Mistral AI
model_name: Mistral 7B Instruct v0.1
model_type: mistral
pipeline_tag: text-generation
tags:
  - finetuned
quantized_by: Second State Inc.

Mistral-7B-Instruct-v0.1-GGUF

Original Model

mistralai/Mistral-7B-Instruct-v0.1

Run with LlamaEdge

LlamaEdge version: v0.2.8 and above
Prompt template
- Prompt type: mistral-instruct
- Prompt string
```
<s>[INST] {prompt} [/INST]
```
Context size: 4096

Run as LlamaEdge service

wasmedge --dir .:. --nn-preload default:GGML:AUTO:Mistral-7B-Instruct-v0.1-Q5_K_M.gguf llama-api-server.wasm -p mistral-instruct

Run as LlamaEdge command app

wasmedge --dir .:. --nn-preload default:GGML:AUTO:Mistral-7B-Instruct-v0.1-Q5_K_M.gguf llama-chat.wasm -p mistral-instruct

Quantized GGUF Models

Name	Quant method	Bits	Size	Use case
Mistral-7B-Instruct-v0.1-Q2_K.gguf	Q2_K	2	2.7 GB	smallest, significant quality loss - not recommended for most purposes
Mistral-7B-Instruct-v0.1-Q3_K_L.gguf	Q3_K_L	3	3.82 GB	small, substantial quality loss
Mistral-7B-Instruct-v0.1-Q3_K_M.gguf	Q3_K_M	3	3.52 GB	very small, high quality loss
Mistral-7B-Instruct-v0.1-Q3_K_S.gguf	Q3_K_S	3	3.16 GB	very small, high quality loss
Mistral-7B-Instruct-v0.1-Q4_0.gguf	Q4_0	4	4.11 GB	legacy; small, very high quality loss - prefer using Q3_K_M
Mistral-7B-Instruct-v0.1-Q4_K_M.gguf	Q4_K_M	4	4.37 GB	medium, balanced quality - recommended
Mistral-7B-Instruct-v0.1-Q4_K_S.gguf	Q4_K_S	4	4.14 GB	small, greater quality loss
Mistral-7B-Instruct-v0.1-Q5_0.gguf	Q5_0	5	5 GB	legacy; medium, balanced quality - prefer using Q4_K_M
Mistral-7B-Instruct-v0.1-Q5_K_M.gguf	Q5_K_M	5	5.13 GB	large, very low quality loss - recommended
Mistral-7B-Instruct-v0.1-Q5_K_S.gguf	Q5_K_S	5	5 GB	large, low quality loss - recommended
Mistral-7B-Instruct-v0.1-Q6_K.gguf	Q6_K	6	5.94 GB	very large, extremely low quality loss
Mistral-7B-Instruct-v0.1-Q8_0.gguf	Q8_0	8	7.7 GB	very large, extremely low quality loss - not recommended