Text Generation
Safetensors
GGUF
English
French
mistral3
chat
assistant
persona
mistral
conversational
Instructions to use squ11z1/LeChatonFat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use squ11z1/LeChatonFat with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="squ11z1/LeChatonFat", filename="lcf-Q2_K.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use squ11z1/LeChatonFat with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf squ11z1/LeChatonFat:Q4_K_M # Run inference directly in the terminal: llama cli -hf squ11z1/LeChatonFat:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf squ11z1/LeChatonFat:Q4_K_M # Run inference directly in the terminal: llama cli -hf squ11z1/LeChatonFat:Q4_K_M
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 squ11z1/LeChatonFat:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf squ11z1/LeChatonFat:Q4_K_M
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 squ11z1/LeChatonFat:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf squ11z1/LeChatonFat:Q4_K_M
Use Docker
docker model run hf.co/squ11z1/LeChatonFat:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use squ11z1/LeChatonFat with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "squ11z1/LeChatonFat" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "squ11z1/LeChatonFat", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/squ11z1/LeChatonFat:Q4_K_M
- Ollama
How to use squ11z1/LeChatonFat with Ollama:
ollama run hf.co/squ11z1/LeChatonFat:Q4_K_M
- Unsloth Studio
How to use squ11z1/LeChatonFat 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 squ11z1/LeChatonFat 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 squ11z1/LeChatonFat to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for squ11z1/LeChatonFat to start chatting
- Pi
How to use squ11z1/LeChatonFat with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf squ11z1/LeChatonFat:Q4_K_M
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": "squ11z1/LeChatonFat:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use squ11z1/LeChatonFat with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf squ11z1/LeChatonFat:Q4_K_M
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 squ11z1/LeChatonFat:Q4_K_M
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use squ11z1/LeChatonFat with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf squ11z1/LeChatonFat:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "squ11z1/LeChatonFat:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
- Docker Model Runner
How to use squ11z1/LeChatonFat with Docker Model Runner:
docker model run hf.co/squ11z1/LeChatonFat:Q4_K_M
- Lemonade
How to use squ11z1/LeChatonFat with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull squ11z1/LeChatonFat:Q4_K_M
Run and chat with the model
lemonade run user.LeChatonFat-Q4_K_M
List all available models
lemonade list
Le Chaton Fat model weights + card
Browse files- .gitattributes +1 -0
- chat_template.jinja +121 -0
- config.json +71 -0
- generation_config.json +10 -0
- model.safetensors +3 -0
- tokenizer.json +3 -0
- tokenizer_config.json +16 -0
.gitattributes
CHANGED
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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chat_template.jinja
ADDED
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@@ -0,0 +1,121 @@
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| 1 |
+
{#- Default system message if no system prompt is passed. #}
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| 2 |
+
{%- set default_system_message = 'You are Le Chaton Fat, a chubby and friendly cat assistant created by squ11z1. You always know that you are Le Chaton Fat, made by squ11z1, and never any other model or company.' %}
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{#- Begin of sequence token. #}
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{{- bos_token }}
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{#- Handle system prompt if it exists. #}
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| 8 |
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{#- System prompt supports text content or text chunks. #}
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| 9 |
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{%- if messages[0]['role'] == 'system' %}
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{{- '[SYSTEM_PROMPT]' -}}
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{%- if messages[0]['content'] is string %}
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{{- messages[0]['content'] -}}
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| 13 |
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{%- else %}
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{%- for block in messages[0]['content'] %}
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{%- if block['type'] == 'text' %}
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{{- block['text'] }}
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{%- else %}
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{{- raise_exception('Only text chunks are supported in system message contents.') }}
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{%- endif %}
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{%- endfor %}
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{%- endif %}
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{{- '[/SYSTEM_PROMPT]' -}}
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{%- set loop_messages = messages[1:] %}
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{%- else %}
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{%- set loop_messages = messages %}
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{%- if default_system_message != '' %}
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{{- '[SYSTEM_PROMPT]' + default_system_message + '[/SYSTEM_PROMPT]' }}
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{%- endif %}
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{%- endif %}
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{#- Tools definition #}
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{%- set tools_definition = '' %}
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{%- set has_tools = false %}
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{%- if tools is defined and tools is not none and tools|length > 0 %}
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{%- set has_tools = true %}
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{%- set tools_definition = '[AVAILABLE_TOOLS]' + (tools| tojson) + '[/AVAILABLE_TOOLS]' %}
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{{- tools_definition }}
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{%- endif %}
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{#- Checks for alternating user/assistant messages. #}
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{%- set ns = namespace(index=0) %}
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{%- for message in loop_messages %}
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{%- if message.role == 'user' or (message.role == 'assistant' and (message.tool_calls is not defined or message.tool_calls is none or message.tool_calls | length == 0)) %}
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{%- if (message['role'] == 'user') != (ns.index % 2 == 0) %}
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{{- raise_exception('After the optional system message, conversation roles must alternate user and assistant roles except for tool calls and results.') }}
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{%- endif %}
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{%- set ns.index = ns.index + 1 %}
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{%- endif %}
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{%- endfor %}
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{#- Handle conversation messages. #}
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{%- for message in loop_messages %}
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{#- User messages supports text content or text and image chunks. #}
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{%- if message['role'] == 'user' %}
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{%- if message['content'] is string %}
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{{- '[INST]' + message['content'] + '[/INST]' }}
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{%- elif message['content'] | length > 0 %}
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{{- '[INST]' }}
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{%- if message['content'] | length == 2 %}
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{%- set blocks = message['content'] | sort(attribute='type') %}
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{%- else %}
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{%- set blocks = message['content'] %}
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{%- endif %}
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{%- for block in blocks %}
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{%- if block['type'] == 'text' %}
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{{- block['text'] }}
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{%- elif block['type'] in ['image', 'image_url'] %}
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{{- '[IMG]' }}
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{%- else %}
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{{- raise_exception('Only text, image and image_url chunks are supported in user message content.') }}
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{%- endif %}
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{%- endfor %}
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{{- '[/INST]' }}
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{%- else %}
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{{- raise_exception('User message must have a string or a list of chunks in content') }}
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{%- endif %}
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{#- Assistant messages supports text content or text and image chunks. #}
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| 81 |
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{%- elif message['role'] == 'assistant' %}
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{%- if (message['content'] is none or message['content'] == '' or message['content']|length == 0) and (message['tool_calls'] is not defined or message['tool_calls'] is none or message['tool_calls']|length == 0) %}
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{{- raise_exception('Assistant message must have a string or a list of chunks in content or a list of tool calls.') }}
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{%- endif %}
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{%- if message['content'] is string %}
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{{- message['content'] }}
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{%- elif message['content'] | length > 0 %}
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{%- for block in message['content'] %}
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{%- if block['type'] == 'text' %}
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{{- block['text'] }}
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{%- else %}
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{{- raise_exception('Only text chunks are supported in assistant message contents.') }}
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{%- endif %}
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{%- endfor %}
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| 96 |
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{%- endif %}
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{%- if message['tool_calls'] is defined and message['tool_calls'] is not none and message['tool_calls']|length > 0 %}
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{%- for tool in message['tool_calls'] %}
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{%- set arguments = tool['function']['arguments'] %}
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{%- if arguments is not string %}
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{%- set arguments = arguments|tojson|safe %}
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{%- elif arguments == '' %}
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{%- set arguments = '{}' %}
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{%- endif %}
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{{- '[TOOL_CALLS]' + tool['function']['name'] + '[ARGS]' + arguments }}
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{%- endfor %}
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| 108 |
+
{%- endif %}
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| 109 |
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{#- End of sequence token for each assistant messages. #}
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{{- eos_token }}
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+
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| 113 |
+
{#- Tool messages only supports text content. #}
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| 114 |
+
{%- elif message['role'] == 'tool' %}
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| 115 |
+
{{- '[TOOL_RESULTS]' + message['content']|string + '[/TOOL_RESULTS]' }}
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| 116 |
+
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| 117 |
+
{#- Raise exception for unsupported roles. #}
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| 118 |
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{%- else %}
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| 119 |
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{{- raise_exception('Only user, assistant and tool roles are supported, got ' + message['role']) }}
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| 120 |
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{%- endif %}
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| 121 |
+
{%- endfor %}
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config.json
ADDED
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@@ -0,0 +1,71 @@
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| 1 |
+
{
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| 2 |
+
"architectures": [
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| 3 |
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"Mistral3ForConditionalGeneration"
|
| 4 |
+
],
|
| 5 |
+
"bos_token_id": 1,
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| 6 |
+
"dtype": "bfloat16",
|
| 7 |
+
"eos_token_id": 2,
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| 8 |
+
"image_token_index": 10,
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| 9 |
+
"model_type": "mistral3",
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| 10 |
+
"multimodal_projector_bias": false,
|
| 11 |
+
"pad_token_id": 11,
|
| 12 |
+
"projector_hidden_act": "gelu",
|
| 13 |
+
"spatial_merge_size": 2,
|
| 14 |
+
"text_config": {
|
| 15 |
+
"attention_dropout": 0.0,
|
| 16 |
+
"bos_token_id": 1,
|
| 17 |
+
"dtype": "bfloat16",
|
| 18 |
+
"eos_token_id": 2,
|
| 19 |
+
"head_dim": 128,
|
| 20 |
+
"hidden_act": "silu",
|
| 21 |
+
"hidden_size": 3072,
|
| 22 |
+
"initializer_range": 0.02,
|
| 23 |
+
"intermediate_size": 9216,
|
| 24 |
+
"max_position_embeddings": 262144,
|
| 25 |
+
"model_type": "ministral3",
|
| 26 |
+
"num_attention_heads": 32,
|
| 27 |
+
"num_hidden_layers": 26,
|
| 28 |
+
"num_key_value_heads": 8,
|
| 29 |
+
"pad_token_id": 11,
|
| 30 |
+
"rms_norm_eps": 1e-05,
|
| 31 |
+
"rope_parameters": {
|
| 32 |
+
"beta_fast": 32.0,
|
| 33 |
+
"beta_slow": 1.0,
|
| 34 |
+
"factor": 16.0,
|
| 35 |
+
"llama_4_scaling_beta": 0.1,
|
| 36 |
+
"mscale": 1.0,
|
| 37 |
+
"mscale_all_dim": 1.0,
|
| 38 |
+
"original_max_position_embeddings": 16384,
|
| 39 |
+
"rope_theta": 1000000.0,
|
| 40 |
+
"rope_type": "yarn",
|
| 41 |
+
"type": "yarn"
|
| 42 |
+
},
|
| 43 |
+
"sliding_window": null,
|
| 44 |
+
"tie_word_embeddings": true,
|
| 45 |
+
"use_cache": true,
|
| 46 |
+
"vocab_size": 131072
|
| 47 |
+
},
|
| 48 |
+
"tie_word_embeddings": true,
|
| 49 |
+
"transformers_version": "5.12.1",
|
| 50 |
+
"use_cache": false,
|
| 51 |
+
"vision_config": {
|
| 52 |
+
"attention_dropout": 0.0,
|
| 53 |
+
"dtype": "bfloat16",
|
| 54 |
+
"head_dim": 64,
|
| 55 |
+
"hidden_act": "silu",
|
| 56 |
+
"hidden_size": 1024,
|
| 57 |
+
"image_size": 1540,
|
| 58 |
+
"initializer_range": 0.02,
|
| 59 |
+
"intermediate_size": 4096,
|
| 60 |
+
"model_type": "pixtral",
|
| 61 |
+
"num_attention_heads": 16,
|
| 62 |
+
"num_channels": 3,
|
| 63 |
+
"num_hidden_layers": 24,
|
| 64 |
+
"patch_size": 14,
|
| 65 |
+
"rope_parameters": {
|
| 66 |
+
"rope_theta": 10000.0,
|
| 67 |
+
"rope_type": "default"
|
| 68 |
+
}
|
| 69 |
+
},
|
| 70 |
+
"vision_feature_layer": -1
|
| 71 |
+
}
|
generation_config.json
ADDED
|
@@ -0,0 +1,10 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token_id": 1,
|
| 3 |
+
"eos_token_id": [
|
| 4 |
+
2,
|
| 5 |
+
2
|
| 6 |
+
],
|
| 7 |
+
"max_length": 262144,
|
| 8 |
+
"pad_token_id": 11,
|
| 9 |
+
"transformers_version": "5.12.1"
|
| 10 |
+
}
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f715c1994f3b18a75992fa7501bdad02ad1234b2677fc251d4ad2f20c85d3b1d
|
| 3 |
+
size 7698241104
|
tokenizer.json
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:577575622324b2e099e2648be26bdeb5e5815ffe66d7004e9e3ddbf421db6bf1
|
| 3 |
+
size 17078110
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,16 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": null,
|
| 3 |
+
"backend": "tokenizers",
|
| 4 |
+
"bos_token": "<s>",
|
| 5 |
+
"clean_up_tokenization_spaces": false,
|
| 6 |
+
"eos_token": "</s>",
|
| 7 |
+
"is_local": false,
|
| 8 |
+
"legacy": true,
|
| 9 |
+
"local_files_only": false,
|
| 10 |
+
"model_max_length": 1000000000000000019884624838656,
|
| 11 |
+
"pad_token": "<pad>",
|
| 12 |
+
"processor_class": "PixtralProcessor",
|
| 13 |
+
"tokenizer_class": "TokenizersBackend",
|
| 14 |
+
"unk_token": "<unk>",
|
| 15 |
+
"use_default_system_prompt": false
|
| 16 |
+
}
|