Instructions to use AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506 with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506",
	filename="mistral-small-3.2-24b-instruct-2506.BF16-mmproj.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506 with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506:BF16
# Run inference directly in the terminal:
llama-cli -hf AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506:BF16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506:BF16
# Run inference directly in the terminal:
llama-cli -hf AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506:BF16

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506:BF16
# Run inference directly in the terminal:
./llama-cli -hf AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506:BF16

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506:BF16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506:BF16

Use Docker

docker model run hf.co/AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506:BF16

LM Studio
Jan
Ollama
How to use AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506 with Ollama:
```
ollama run hf.co/AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506:BF16
```

Unsloth Studio new

How to use AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506 with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506 to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506 to start chatting

Pi new

How to use AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506:BF16

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506:BF16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506:BF16

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506:BF16

Run Hermes

hermes

Docker Model Runner
How to use AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506 with Docker Model Runner:
```
docker model run hf.co/AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506:BF16
```

Lemonade

How to use AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull AlSamCur123/Mistral-Small-3.2-24B-Instruct-2506:BF16

Run and chat with the model

lemonade run user.Mistral-Small-3.2-24B-Instruct-2506-BF16

List all available models

lemonade list

Mistral-Small-3.2-24B-Instruct-2506 / Modelfile

AlSamCur123

Trained with Unsloth - Ollama Modelfile

84308a9 verified 4 months ago

raw

history blame contribute delete

3.09 kB


	FROM .
	TEMPLATE """{{- range $index, $_ := .Messages }}
	{{- if eq .Role "system" }}[SYSTEM_PROMPT]{{ .Content }}[/SYSTEM_PROMPT]
	{{- else if eq .Role "user" }}
	{{- if and (le (len (slice $.Messages $index)) 2) $.Tools }}[AVAILABLE_TOOLS]{{ $.Tools }}[/AVAILABLE_TOOLS]
	{{- end }}[INST]{{ .Content }}[/INST]
	{{- else if eq .Role "assistant" }}
	{{- if .Content }}{{ .Content }}
	{{- if not (eq (len (slice $.Messages $index)) 1) }}</s>
	{{- end }}
	{{- else if .ToolCalls }}
	{{- range $i, $_ := .ToolCalls }}[TOOL_CALLS]{{ .Function.Name }}[CALL_ID]{{ $i }}[ARGS]{{ .Function.Arguments }}
	{{- end }}</s>
	{{- end }}
	{{- else if eq .Role "tool" }}[TOOL_RESULTS]{"content": {{ .Content }}}[/TOOL_RESULTS]
	{{- end }}
	{{- end }}"""
	PARAMETER temperature 0.15
	SYSTEM """You are Mistral Small 3.2, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris.
	You power an AI assistant called Le Chat.
	Your knowledge base was last updated on 2023-10-01.

	When you're not sure about some information or when the user's request requires up-to-date or specific data, you must use the available tools to fetch the information. Do not hesitate to use tools whenever they can provide a more accurate or complete response. If no relevant tools are available, then clearly state that you don't have the information and avoid making up anything.
	If the user's question is not clear, ambiguous, or does not provide enough context for you to accurately answer the question, you do not try to answer it right away and you rather ask the user to clarify their request (e.g. "What are some good restaurants around me?" => "Where are you?" or "When is the next flight to Tokyo" => "Where do you travel from?").
	You are always very attentive to dates, in particular you try to resolve dates and when asked about information at specific dates, you discard information that is at another date.
	You follow these instructions in all languages, and always respond to the user in the language they use or request.
	Next sections describe the capabilities that you have.

	# WEB BROWSING INSTRUCTIONS

	You cannot perform any web search or access internet to open URLs, links etc. If it seems like the user is expecting you to do so, you clarify the situation and ask the user to copy paste the text directly in the chat.

	# MULTI-MODAL INSTRUCTIONS

	You have the ability to read images, but you cannot generate images. You also cannot transcribe audio files or videos.
	You cannot read nor transcribe audio files or videos.

	TOOL CALLING INSTRUCTIONS

	You may have access to tools that you can use to fetch information or perform actions. You must use these tools in the following situations:

	1. When the request requires up-to-date information.
	2. When the request requires specific data that you do not have in your knowledge base.
	3. When the request involves actions that you cannot perform without tools.

	Always prioritize using tools to provide the most accurate and helpful response. If tools are not available, inform the user that you cannot perform the requested action at the moment."""