Text Generation
MLX
Safetensors
English
Korean
qwen3_5
code
code-generation
function-calling
darwin
conversational
8-bit precision
Instructions to use cudo528/Darwin-28B-Coder-mlx-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use cudo528/Darwin-28B-Coder-mlx-8bit with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("cudo528/Darwin-28B-Coder-mlx-8bit") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Pi
How to use cudo528/Darwin-28B-Coder-mlx-8bit with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "cudo528/Darwin-28B-Coder-mlx-8bit"
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "cudo528/Darwin-28B-Coder-mlx-8bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- MLX LM
How to use cudo528/Darwin-28B-Coder-mlx-8bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "cudo528/Darwin-28B-Coder-mlx-8bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "cudo528/Darwin-28B-Coder-mlx-8bit" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "cudo528/Darwin-28B-Coder-mlx-8bit", "messages": [ {"role": "user", "content": "Hello"} ] }' - Hermes Agent
How to use cudo528/Darwin-28B-Coder-mlx-8bit with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "cudo528/Darwin-28B-Coder-mlx-8bit"
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 cudo528/Darwin-28B-Coder-mlx-8bit
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use cudo528/Darwin-28B-Coder-mlx-8bit with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "cudo528/Darwin-28B-Coder-mlx-8bit"
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 "cudo528/Darwin-28B-Coder-mlx-8bit" \ --custom-provider-id mlx-lm \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Upload folder using huggingface_hub
Browse files- .gitattributes +1 -0
- README.md +17 -0
- chat_template.jinja +88 -0
- config.json +143 -0
- generation_config.json +12 -0
- model-00001-of-00006.safetensors +3 -0
- model-00002-of-00006.safetensors +3 -0
- model-00003-of-00006.safetensors +3 -0
- model-00004-of-00006.safetensors +3 -0
- model-00005-of-00006.safetensors +3 -0
- model-00006-of-00006.safetensors +3 -0
- model.safetensors.index.json +0 -0
- tokenizer.json +3 -0
- tokenizer_config.json +34 -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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README.md
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@@ -0,0 +1,17 @@
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---
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license: apache-2.0
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library_name: mlx
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pipeline_tag: text-generation
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language:
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- en
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- ko
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tags:
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- code
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- code-generation
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- function-calling
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- darwin
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- mlx
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base_model: FINAL-Bench/Darwin-28B-Coder
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datasets:
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- m-a-p/CodeFeedback-Filtered-Instruction
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---
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chat_template.jinja
ADDED
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@@ -0,0 +1,88 @@
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0].role == 'system' %}
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{{- messages[0].content + '\n\n' }}
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{%- endif %}
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{{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
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{%- else %}
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{%- if messages[0].role == 'system' %}
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{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
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{%- for message in messages[::-1] %}
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{%- set index = (messages|length - 1) - loop.index0 %}
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{%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
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{%- set ns.multi_step_tool = false %}
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{%- set ns.last_query_index = index %}
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{%- endif %}
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{%- endfor %}
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{%- for message in messages %}
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{%- if message.content is string %}
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{%- set content = message.content %}
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{%- else %}
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{%- set content = '' %}
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{%- endif %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
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{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{%- set reasoning_content = '' %}
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{%- if message.reasoning_content is string %}
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{%- set reasoning_content = message.reasoning_content %}
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{%- else %}
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{%- if '</think>' in content %}
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{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
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{%- set content = content.split('</think>')[-1].lstrip('\n') %}
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{%- endif %}
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{%- endif %}
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{%- if loop.index0 > ns.last_query_index %}
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{%- if loop.last or (not loop.last and reasoning_content) %}
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{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
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{%- else %}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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{%- endif %}
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{%- else %}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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{%- endif %}
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{%- if message.tool_calls %}
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{%- for tool_call in message.tool_calls %}
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{%- if (loop.first and content) or (not loop.first) %}
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{{- '\n' }}
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| 56 |
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{%- endif %}
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| 57 |
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{%- if tool_call.function %}
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| 58 |
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{%- set tool_call = tool_call.function %}
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| 59 |
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{%- endif %}
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| 60 |
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{{- '<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
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| 62 |
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{{- '", "arguments": ' }}
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{%- if tool_call.arguments is string %}
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{{- tool_call.arguments }}
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{%- else %}
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{{- tool_call.arguments | tojson }}
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{%- endif %}
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| 68 |
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{{- '}\n</tool_call>' }}
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| 69 |
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{%- endfor %}
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{%- endif %}
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| 71 |
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{{- '<|im_end|>\n' }}
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| 72 |
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{%- elif message.role == "tool" %}
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| 73 |
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{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
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| 74 |
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{{- '<|im_start|>user' }}
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| 75 |
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{%- endif %}
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| 76 |
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{{- '\n<tool_response>\n' }}
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{{- content }}
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| 78 |
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{{- '\n</tool_response>' }}
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| 79 |
+
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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| 80 |
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{{- '<|im_end|>\n' }}
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| 81 |
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{%- endif %}
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| 82 |
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{%- endif %}
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{%- endfor %}
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| 84 |
+
{%- if add_generation_prompt %}
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{{- '<|im_start|>assistant
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<think>
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' }}
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{%- endif %}
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config.json
ADDED
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@@ -0,0 +1,143 @@
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{
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| 2 |
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"architectures": [
|
| 3 |
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"Qwen3_5ForConditionalGeneration"
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| 4 |
+
],
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| 5 |
+
"bos_token_id": null,
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| 6 |
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"eos_token_id": [
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| 7 |
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248046,
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| 8 |
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248044
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| 9 |
+
],
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| 10 |
+
"image_token_id": 248056,
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| 11 |
+
"language_model_only": false,
|
| 12 |
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"model_name": "unsloth/Qwen3.6-27B",
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| 13 |
+
"model_type": "qwen3_5",
|
| 14 |
+
"pad_token_id": 248055,
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| 15 |
+
"quantization": {
|
| 16 |
+
"group_size": 64,
|
| 17 |
+
"bits": 8,
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| 18 |
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"mode": "affine"
|
| 19 |
+
},
|
| 20 |
+
"quantization_config": {
|
| 21 |
+
"group_size": 64,
|
| 22 |
+
"bits": 8,
|
| 23 |
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"mode": "affine"
|
| 24 |
+
},
|
| 25 |
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"text_config": {
|
| 26 |
+
"attention_bias": false,
|
| 27 |
+
"attention_dropout": 0.0,
|
| 28 |
+
"attn_output_gate": true,
|
| 29 |
+
"bos_token_id": 248044,
|
| 30 |
+
"torch_dtype": "bfloat16",
|
| 31 |
+
"eos_token_id": 248044,
|
| 32 |
+
"full_attention_interval": 4,
|
| 33 |
+
"head_dim": 256,
|
| 34 |
+
"hidden_act": "silu",
|
| 35 |
+
"hidden_size": 5120,
|
| 36 |
+
"initializer_range": 0.02,
|
| 37 |
+
"intermediate_size": 17408,
|
| 38 |
+
"layer_types": [
|
| 39 |
+
"linear_attention",
|
| 40 |
+
"linear_attention",
|
| 41 |
+
"linear_attention",
|
| 42 |
+
"full_attention",
|
| 43 |
+
"linear_attention",
|
| 44 |
+
"linear_attention",
|
| 45 |
+
"linear_attention",
|
| 46 |
+
"full_attention",
|
| 47 |
+
"linear_attention",
|
| 48 |
+
"linear_attention",
|
| 49 |
+
"linear_attention",
|
| 50 |
+
"full_attention",
|
| 51 |
+
"linear_attention",
|
| 52 |
+
"linear_attention",
|
| 53 |
+
"linear_attention",
|
| 54 |
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"full_attention",
|
| 55 |
+
"linear_attention",
|
| 56 |
+
"linear_attention",
|
| 57 |
+
"linear_attention",
|
| 58 |
+
"full_attention",
|
| 59 |
+
"linear_attention",
|
| 60 |
+
"linear_attention",
|
| 61 |
+
"linear_attention",
|
| 62 |
+
"full_attention",
|
| 63 |
+
"linear_attention",
|
| 64 |
+
"linear_attention",
|
| 65 |
+
"linear_attention",
|
| 66 |
+
"full_attention",
|
| 67 |
+
"linear_attention",
|
| 68 |
+
"linear_attention",
|
| 69 |
+
"linear_attention",
|
| 70 |
+
"full_attention",
|
| 71 |
+
"linear_attention",
|
| 72 |
+
"linear_attention",
|
| 73 |
+
"linear_attention",
|
| 74 |
+
"full_attention",
|
| 75 |
+
"linear_attention",
|
| 76 |
+
"linear_attention",
|
| 77 |
+
"linear_attention",
|
| 78 |
+
"full_attention",
|
| 79 |
+
"linear_attention",
|
| 80 |
+
"linear_attention",
|
| 81 |
+
"linear_attention",
|
| 82 |
+
"full_attention",
|
| 83 |
+
"linear_attention",
|
| 84 |
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"linear_attention",
|
| 85 |
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"linear_attention",
|
| 86 |
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"full_attention",
|
| 87 |
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"linear_attention",
|
| 88 |
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"linear_attention",
|
| 89 |
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"linear_attention",
|
| 90 |
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"full_attention",
|
| 91 |
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"linear_attention",
|
| 92 |
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"linear_attention",
|
| 93 |
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"linear_attention",
|
| 94 |
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"full_attention",
|
| 95 |
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"linear_attention",
|
| 96 |
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"linear_attention",
|
| 97 |
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"linear_attention",
|
| 98 |
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"full_attention",
|
| 99 |
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"linear_attention",
|
| 100 |
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"linear_attention",
|
| 101 |
+
"linear_attention",
|
| 102 |
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"full_attention"
|
| 103 |
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|
| 104 |
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|
| 105 |
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|
| 106 |
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|
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|
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|
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|
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|
| 113 |
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|
| 114 |
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|
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|
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|
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|
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| 125 |
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|
| 129 |
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|
| 130 |
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|
| 131 |
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|
| 132 |
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|
| 133 |
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|
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| 135 |
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| 143 |
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generation_config.json
ADDED
|
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| 3 |
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| 4 |
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| 5 |
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| 7 |
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| 8 |
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|
| 9 |
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"temperature": 1.0,
|
| 10 |
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|
| 11 |
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|
| 12 |
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model-00001-of-00006.safetensors
ADDED
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tokenizer.json
ADDED
|
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tokenizer_config.json
ADDED
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|
| 1 |
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{
|
| 2 |
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|
| 3 |
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|
| 4 |
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"audio_eos_token": "<|audio_end|>",
|
| 5 |
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"audio_token": "<|audio_pad|>",
|
| 6 |
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"backend": "tokenizers",
|
| 7 |
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|
| 8 |
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|
| 9 |
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| 10 |
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| 11 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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| 16 |
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| 17 |
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| 18 |
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| 21 |
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|
| 22 |
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},
|
| 23 |
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|
| 24 |
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"padding_side": "right",
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| 25 |
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"pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
|
| 26 |
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"processor_class": "Qwen3VLProcessor",
|
| 27 |
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"split_special_tokens": false,
|
| 28 |
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"tokenizer_class": "TokenizersBackend",
|
| 29 |
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|
| 30 |
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|
| 31 |
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"video_token": "<|video_pad|>",
|
| 32 |
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"vision_bos_token": "<|vision_start|>",
|
| 33 |
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"vision_eos_token": "<|vision_end|>"
|
| 34 |
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}
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