Mistral AI · 7B · Dense
High-quality 7B with sliding window attention
1.6M downloads
2.5K likes
2024-05 32K context
Use Cases
chat reasoning
| Quant | Bits | VRAM | Quality | Status |
|---|---|---|---|---|
| Q2_K | 2 | 2.7 GB | low | — |
| Q3_K_M | 3 | 3.6 GB | moderate | — |
| Q4_K_M | 4 | 4.1 GB | good | — |
| Q5_K_M | 5 | 5 GB | good | — |
| Q6_K | 6 | 5.9 GB | excellent | — |
| Q8_0 | 8 | 7.7 GB | excellent | — |
| F16 | 16 | 14.8 GB | lossless | — |
About this model
Mistral is a 7B parameter model, distributed with the Apache license. It is available in both instruct (instruction following) and text completion.
The Mistral AI team has noted that Mistral 7B:
- Outperforms Llama 2 13B on all benchmarks
- Outperforms Llama 1 34B on many benchmarks
- Approaches CodeLlama 7B performance on code, while remaining good at English tasks
Versions
| Tag | Date | Notes |
|---|---|---|
v0.3 latest |
05/22/2024 | A new version of Mistral 7B that supports function calling. |
v0.2 |
03/23/2024 | A minor release of Mistral 7B |
v0.1 |
09/27/2023 | Initial release |
Function calling
Mistral 0.3 supports function calling with Ollama’s raw mode.
Example raw prompt
[AVAILABLE_TOOLS] [{"type": "function", "function": {"name": "get_current_weather", "description": "Get the current weather", "parameters": {"type": "object", "properties": {"location": {"type": "string", "description": "The city and state, e.g. San Francisco, CA"}, "format": {"type": "string", "enum": ["celsius", "fahrenheit"], "description": "The temperature unit to use. Infer this from the users location."}}, "required": ["location", "format"]}}}][/AVAILABLE_TOOLS][INST] What is the weather like today in San Francisco [/INST]
Example response
[TOOL_CALLS] [{"name": "get_current_weather", "arguments": {"location": "San Francisco, CA", "format": "celsius"}}]
For more information on raw mode, see the API documentation.
Variations
instruct |
Instruct models follow instructions |
text |
Text models are the base foundation model without any fine-tuning for conversations, and are best used for simple text completion. |
Usage
CLI
Instruct:
ollama run mistral
API
Example:
curl -X POST http://localhost:11434/api/generate -d '{
"model": "mistral",
"prompt":"Here is a story about llamas eating grass"
}'