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Model: tocchitocchi/Qwen3-Swallow-32B-RL-v0.2-MLX-fp16
Source: Original Platform

.gitattributes

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README.md

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+---
+license: apache-2.0
+base_model:
+- tokyotech-llm/Qwen3-Swallow-32B-RL-v0.2
+library_name: mlx
+tags:
+- mlx
+- quantized
+- apple-silicon
+- japanese
+- swallow
+language:
+- ja
+- en
+pipeline_tag: text-generation
+---
+
+# Qwen3-Swallow-32B-RL-v0.2-MLX-fp16
+
+This model is an [MLX](https://github.com/ml-explore/mlx) format conversion of [`tokyotech-llm/Qwen3-Swallow-32B-RL-v0.2`](https://huggingface.co/tokyotech-llm/Qwen3-Swallow-32B-RL-v0.2), optimized for Apple Silicon.
+
+## Model Details
+
+| Attribute | Value |
+|---|---|
+| **Original Model** | [`tokyotech-llm/Qwen3-Swallow-32B-RL-v0.2`](https://huggingface.co/tokyotech-llm/Qwen3-Swallow-32B-RL-v0.2) |
+| **Architecture** | Dense Transformer |
+| **Parameters** | 32B |
+| **Quantization** | Full precision (fp16) |
+| **Model Size** | ~61 GB |
+| **Format** | MLX (Apple Silicon optimized) |
+| **Converted with** | mlx-lm v0.30.8 |
+| **License** | Apache 2.0 |
+
+## About Qwen3-Swallow
+
+Qwen3-Swallow is a bilingual Japanese-English large language model developed by the [Swallow Project](https://swallow-llm.github.io/) at the Institute of Science Tokyo (formerly Tokyo Institute of Technology) and AIST. Built upon Qwen3 through Continual Pre-Training (CPT), Supervised Fine-Tuning (SFT), and Reinforcement Learning (RL), it achieves strong performance on both Japanese and English tasks while maintaining capabilities in mathematics and coding.
+
+For more details, see the [original model card](https://huggingface.co/tokyotech-llm/Qwen3-Swallow-32B-RL-v0.2).
+
+## Usage
+
+### Quick Start (Python)
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("tocchitocchi/Qwen3-Swallow-32B-RL-v0.2-MLX-fp16")
+
+messages = [{"role": "user", "content": "hello"}]
+prompt = tokenizer.apply_chat_template(
+    messages, add_generation_prompt=True
+)
+
+response = generate(model, tokenizer, prompt=prompt, verbose=True, max_tokens=512)
+```
+
+### Interactive Chat
+
+```bash
+mlx_lm.chat --model tocchitocchi/Qwen3-Swallow-32B-RL-v0.2-MLX-fp16
+```
+
+### OpenAI-Compatible Server
+
+```bash
+mlx_lm.server --model tocchitocchi/Qwen3-Swallow-32B-RL-v0.2-MLX-fp16 --port 8080
+```
+
+Then connect with any OpenAI-compatible client at `http://localhost:8080/v1`.
+
+## Acknowledgments
+
+- Original model by [Swallow Project](https://swallow-llm.github.io/) (Institute of Science Tokyo and AIST)
+- MLX framework by [Apple Machine Learning Research](https://github.com/ml-explore/mlx)
+- Conversion performed using [mlx-lm](https://github.com/ml-explore/mlx-lm)

chat_template.jinja

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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {{- messages[0].content + '\n\n' }}
+    {%- endif %}
+    {{- "# 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>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\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" }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- 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>')) %}
+        {%- set ns.multi_step_tool = false %}
+        {%- set ns.last_query_index = index %}
+    {%- endif %}
+{%- endfor %}
+{%- for message in messages %}
+    {%- if message.content is string %}
+        {%- set content = message.content %}
+    {%- else %}
+        {%- set content = '' %}
+    {%- endif %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in content %}
+                {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+                {%- set content = content.split('</think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {%- if loop.last or (not loop.last and reasoning_content) %}
+                {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
+            {%- else %}
+                {{- '<|im_start|>' + message.role + '\n' + content }}
+            {%- endif %}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and content) or (not loop.first) %}
+                    {{- '\n' }}
+                {%- endif %}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<tool_call>\n{"name": "' }}
+                {{- tool_call.name }}
+                {{- '", "arguments": ' }}
+                {%- if tool_call.arguments is string %}
+                    {{- tool_call.arguments }}
+                {%- else %}
+                    {{- tool_call.arguments | tojson }}
+                {%- endif %}
+                {{- '}\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- endif %}
+{%- endif %}

config.json

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+{
+    "architectures": [
+        "Qwen3ForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "bos_token_id": 151643,
+    "dtype": "bfloat16",
+    "eos_token_id": [
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+    "head_dim": 128,
+    "hidden_act": "silu",
+    "hidden_size": 5120,
+    "initializer_range": 0.02,
+    "intermediate_size": 25600,
+    "layer_types": [
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+    "max_position_embeddings": 40960,
+    "max_window_layers": 64,
+    "model_type": "qwen3",
+    "num_attention_heads": 64,
+    "num_hidden_layers": 64,
+    "num_key_value_heads": 8,
+    "rms_norm_eps": 1e-06,
+    "rope_scaling": null,
+    "rope_theta": 1000000,
+    "sliding_window": null,
+    "tie_word_embeddings": false,
+    "transformers_version": "4.57.3",
+    "use_cache": true,
+    "use_sliding_window": false,
+    "vocab_size": 151936
+}

generation_config.json

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+  "bos_token_id": 151643,
+  "do_sample": true,
+  "eos_token_id": [
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+  ],
+  "pad_token_id": 151643,
+  "temperature": 0.6,
+  "top_k": 20,
+  "top_p": 0.95,
+  "transformers_version": "4.57.3",
+  "trust_remote_code": false
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