Duplicate from MiniMaxAI/MiniMax-Music3

Co-authored-by: MiniMax <MiniMax-AI@users.noreply.huggingface.co>

.gitattributes

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+*.safetensors filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.wav filter=lfs diff=lfs merge=lfs -text
+qwen_7B/qwen3-8B-tokenizer-music/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+figures/*.png filter=lfs diff=lfs merge=lfs -text
+tokenizer/tokenizer.json filter=lfs diff=lfs merge=lfs -text

LICENSE

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+MiniMax-Music3 COMMUNITY LICENSE
+
+Copyright (c) 2026 MiniMax
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of this Software,
+including the model weights, parameters, configuration files, inference code and associated
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+and to permit persons to whom the Software is furnished to do so, subject to the following
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+
+1. The above copyright notice and this permission notice shall be included in all copies or
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+2. Your use of the Software must comply with applicable laws and regulations (including
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+
+3. Commercial Terms
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+
+Please note that MiniMax-Music3 was fine-tuned from Qwen3-8B (https://huggingface.co/Qwen/Qwen3-8B),
+which is licensed under the Apache License 2.0
+(https://huggingface.co/Qwen/Qwen3-8B/blob/main/LICENSE). DiT-2B was modified from the  Stable Audio
+code (https://github.com/Stability-AI/stable-audio-tools), which is licensed under the MIT License
+(https://github.com/Stability-AI/stable-audio-tools/blob/main/LICENSE). The VAE was modified from
+the DAC code (https://github.com/descriptinc/descript-audio-codec), which is licensed under the MIT
+License (https://github.com/descriptinc/descript-audio-codec/blob/main/LICENSE).
+
+Exhibit A — Acceptable Use Policy
+
+MiniMax reserves the right to update this Acceptable Use Policy from time to time.
+
+Last revised: August [6], 2026.
+
+MiniMax is committed to promoting the safe and responsible use of its tools and features. You agree
+not to use the Software and in any of the following ways:
+
+1. Use in any manner that violates any applicable national, federal, state, local, or international
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+18. Use for military purposes; and
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+19. Use to engage in any unauthorized or unlicensed professional activity, including but not limited
+to financial, legal, medical or healthcare, or other professional practice.

README.md

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+---
+library_name: sglang-omni
+pipeline_tag: text-to-audio
+tags:
+  - music-generation
+  - text-to-music
+  - pytorch
+  - sglang-omni
+---
+
+<div align="center">
+  <img width="100%" src="figures/Music3.png" alt="MiniMax">
+</div>
+<p align="center">
+  <a href="https://agent.minimax.io/" target="_blank"><img src="https://img.shields.io/badge/MiniMax%20Agent-FF6C37?logo=minimax&logoColor=white" alt="MiniMax Agent"></a>
+  <a href="https://platform.minimax.io/docs/guides/text-generation" target="_blank"><img src="https://img.shields.io/badge/API-FF6C37?logo=minimax&logoColor=white" alt="API"></a>
+  <a href="https://www.minimax.io" target="_blank"><img src="https://img.shields.io/badge/MiniMax%20Website-FF6C37?logo=minimax&logoColor=white" alt="MiniMax Website"></a>
+  <br>
+  <a href="https://modelscope.cn/organization/minimax" target="_blank" rel="noopener noreferrer"><img alt="ModelScope MiniMax AI" src="https://img.shields.io/badge/ModelScope-MiniMax%20AI-white?labelColor=%23EF3D5D"></a>
+  <a href="https://platform.minimaxi.com/docs/faq/contact-us" target="_blank"><img src="https://img.shields.io/badge/WeChat-07C160?logo=wechat&logoColor=white" alt="WeChat"></a>
+  <a href="https://discord.com/invite/DPC4AHFCBw" target="_blank"><img src="https://img.shields.io/badge/Discord-5865F2?logo=discord&logoColor=white" alt="Discord"></a>
+  <a href="https://huggingface.co/MiniMaxAI" target="_blank"><img src="https://img.shields.io/badge/Hugging%20Face-FFD21E?logo=huggingface&logoColor=black" alt="Hugging Face"></a>
+  <a href="https://github.com/MiniMax-AI/MiniMax-Music3" target="_blank"><img src="https://img.shields.io/badge/GitHub-181717?logo=github&logoColor=white" alt="GitHub"></a>
+  <a href="https://huggingface.co/MiniMaxAI/MiniMax-Music3/blob/main/LICENSE" target="_blank"><img src="https://img.shields.io/badge/LICENSE-4CAF50?logo=creativecommons&logoColor=white" alt="LICENSE"></a>
+</p>
+
+# MiniMax Music 3
+
+**MiniMax Music 3** is a high-performance music generation model for creating complete songs up to **five minutes** long. Conditioned on lyrics and a detailed music description, it generates structurally coherent songs with expressive vocals, evolving arrangements, and stable long-form audio quality.
+
+MiniMax Music 3 combines an **8B Global LLM** for long-range musical structure, a **0.6B Local LLM** for frame-level acoustic detail, and a continuous hidden-state synthesis system based on **Flow Matching** and **Flow-VAE**. The model produces 32 kHz, 16-bit stereo WAV audio.
+## Demo
+
+Explore music generation examples on the [MiniMax Music 3 Demo](https://minimax-ai.github.io/music3-demo/).
+
+<p align="center">
+  <img width="100%" src="figures/music3.0-Architecture-Diagram.png">
+</p>
+
+## Complete Songs with Long-Range Coherence
+
+MiniMax Music 3 natively supports full-song generation up to five minutes. The model maintains musical themes, rhythm, vocal identity, and arrangement progression across long sequences, enabling complete structures such as intro, verse, pre-chorus, chorus, bridge, instrumental break, and outro.
+
+## Fine-Grained Music Control
+
+The model accepts two complementary inputs:
+
+- **Lyrics** define the words to be sung and may include explicit section tags such as `[Intro]`, `[Verse]`, `[Pre-Chorus]`, `[Chorus]`, `[Post-Chorus]`, `[Bridge]`, `[Instrumental]`, `[Solo]`, and `[Outro]`.
+- **Music description** defines the musical style, emotional progression, vocal performance, instrumentation, arrangement, and production profile.
+
+For precise control, we recommend using a Structured Caption with three sections:
+
+- **Global Metadata**: genre, subgenre, BPM, key, scale, emotional progression, listening scenario, and production profile.
+- **Vocal Details**: vocal gender, timbre, performance style, harmony, backing vocals, and vocal effects.
+- **Arrangement**: primary and secondary instruments, section-level instrument evolution, groove, bass, percussion, textures, and spatial effects.
+
+This representation allows the model to follow not only a global style, but also the musical development of the song over time.
+
+## Hybrid-LM
+
+MiniMax Music 3 uses a hierarchical autoregressive architecture that separates global musical modeling from local acoustic modeling.
+
+- The **Global LLM (8B)** predicts the first RVQ codebook frame by frame and models the song's long-range semantic and structural progression.
+- The **Local LLM (0.6B)** predicts the remaining acoustic codebooks within each frame and restores fine-grained acoustic information.
+
+The Global LLM is initialized from Qwen3-8B. During training, its embedding and output layers are first adapted to semantic music tokens. The Global and Local LLMs are then jointly trained to model all RVQ codebooks.
+
+## Continuous Hidden-State Synthesis
+
+Instead of decoding only from discrete RVQ tokens, the synthesis module fuses the final hidden states of the Global and Local LLMs. These continuous representations preserve richer acoustic information for vocal articulation, instrumental texture, and temporal continuity.
+
+The synthesis path is:
+
+```text
+Global and Local LLM hidden states
+                ↓
+       Hidden-state fusion
+                ↓
+     Flow Matching (2.4B)
+                ↓
+        Flow-VAE latent
+                ↓
+    Flow-VAE Decoder (123M)
+                ↓
+       32 kHz stereo audio
+```
+
+The Flow-VAE architecture is adapted from MiniMax Speech and retrained for the dynamic range and spectral characteristics of music.
+
+## Music Tokenizer
+
+The training tokenizer uses eight layers of Residual Vector Quantization (RVQ):
+
+- The first semantic codebook contains **16,384** entries and captures the core musical semantics and structure.
+- The remaining seven acoustic codebooks contain **1,024** entries each and represent residual acoustic details.
+
+Training first optimizes the semantic codebook, then jointly trains all eight codebooks. At inference time, waveform synthesis uses the fused LLM hidden states and does not require the discrete tokenizer decoder.
+
+## How to Use
+
+MiniMax Music 3 is supported by [SGLang-Omni](https://github.com/sgl-project/sglang-omni). Follow the official [installation guide](https://sgl-project.github.io/sglang-omni/get_started/installation.html) to prepare the runtime environment.
+
+### Download the Model
+
+```bash
+hf download MiniMaxAI/MiniMax-Music3 --local-dir /path/to/minimax_ttm
+```
+
+We recommend the following inference frameworks to serve the model:
+
+- [SGLang](https://docs.sglang.io/) \- see [cookbook](https://sgl-project.github.io/sglang-omni/cookbook/minimax_music3.html) 
+
+- [diffusers](https://github.com/huggingface/diffusers) \- see [diffusers docs](https://github.com/huggingface/diffusers/blob/minimax-music3-integration/docs/source/en/api/pipelines/minimax_music3.md)
+
+- [ComfyUI](https://github.com/Comfy-Org/ComfyUI)
+
+
+### Serve with SGLang-Omni
+
+```bash
+sgl-omni serve --model-path MiniMaxAI/MiniMax-Music3 --port 8000
+```
+
+### Generate Music
+
+The service uses the shared speech API. Put the lyrics in `input` and the music description in `instructions`. Put lyric structure tags such as `[Verse]` and `[Chorus]` on their own lines.
+
+```bash
+curl http://127.0.0.1:8000/v1/audio/speech \
+  -H 'Content-Type: application/json' \
+  -d '{
+    "model": "MiniMaxAI/MiniMax-Music3",
+    "input": "[Verse]\nMorning light filtering through the pine\n[Chorus]\nSoftly the world begins to breathe",
+    "instructions": "A warm acoustic pop song with intimate female vocals, fingerpicked guitar, soft piano, and a gradual emotional build into a wide final chorus.",
+    "response_format": "wav",
+    "seed": 7,
+    "max_new_tokens": 750,
+    "stream": false
+  }' \
+  --output minimax_music3.wav
+```
+
+`max_new_tokens` sets the maximum number of audio frames at 25 frames per second. Generation may finish before this limit when the model emits an end-of-audio token. The response is a 32 kHz, 16-bit stereo WAV file.
+
+### Reproducible Example
+
+The following end-to-end example contains the complete lyrics, music description, and generation parameters used to produce the reference audio.
+
+| Use case | Request | Result |
+|---|---|---|
+| Text-to-music | [View script](https://huggingface.co/MiniMaxAI/MiniMax-Music3/blob/main/scripts/end_to_end/minimax_ttm_test.py) | [minimax_ttm.wav](https://huggingface.co/MiniMaxAI/MiniMax-Music3/blob/main/assets/minimax_ttm.wav) |
+
+## 🧨 Diffusers
+
+MiniMax Music 3 is available as a [diffusers](https://github.com/huggingface/diffusers) modular pipeline. Until [huggingface/diffusers#14456](https://github.com/huggingface/diffusers/pull/14456) is merged, install diffusers from the PR commit:
+
+The snippet below fits 24GB+ VRAM GPUs
+
+```bash
+pip install git+https://github.com/huggingface/diffusers@dafe3733fcfdbf3c48915fe77be3aef65b5d6a2d transformers accelerate soundfile
+```
+
+```python
+import soundfile as sf
+import torch
+from diffusers import ModularPipeline
+
+pipe = ModularPipeline.from_pretrained("MiniMaxAI/MiniMax-Music3")
+pipe.load_components(dtype=torch.bfloat16)
+pipe.to("cuda")
+
+lyrics = """[verse]
+Morning light filtering through the pine
+Every quiet street is yours and mine
+[chorus]
+Softly the world begins to breathe"""
+
+prompt = (
+    "Genre: acoustic pop. BPM: 96. Key: C major. Warm and intimate, building gently into the chorus. "
+    "Vocals: soft female lead, close and breathy, light stacked harmonies in the chorus. "
+    "Arrangement: fingerpicked guitar and soft piano; brushed drums and upright bass enter in the chorus."
+)
+
+audio = pipe(
+    prompt=prompt,
+    lyrics=lyrics,
+    audio_duration=60.0,
+    generator=torch.Generator("cuda").manual_seed(7),
+    output="audios",
+)[0]
+
+sf.write("song.wav", audio.T.float().cpu().numpy(), pipe.sampling_rate)
+```
+
+### Low VRAM
+
+The full precision fits under 24GB of VRAM. With automatic CPU offloading, generation takes in ~22 GB; additionally streaming the language model layer by layer makes it fit even 8 GB video cards:
+
+```python
+import torch
+from diffusers import ComponentsManager, ModularPipeline
+from diffusers.hooks import apply_group_offloading
+
+manager = ComponentsManager()
+manager.enable_auto_cpu_offload(device="cuda")
+pipe = ModularPipeline.from_pretrained("MiniMaxAI/MiniMax-Music3", components_manager=manager)
+pipe.load_components(dtype=torch.bfloat16)
+
+# Only needed below ~22 GB of VRAM — slower, but fits in 8 GB.
+apply_group_offloading(
+    pipe.language_model, onload_device=torch.device("cuda"), offload_type="leaf_level", use_stream=True
+)
+
+
+```
+
+## Prompt Enhancement
+
+A concise natural-language description can be used directly. For richer prompts and more precise control, use the provided [`music-caption-rewriter`](https://github.com/MiniMax-AI/MiniMax-Music3/tree/main/skills/music-caption-rewriter) skill to expand it into a Structured Caption containing `Global Metadata`, `Vocal Details`, and `Arrangement`. The skill preserves musical instructions attached to lyric section tags in the arrangement description while keeping the lyric text in the lyrics input.
+
+```bash
+npx skills add MiniMax-AI/MiniMax-Music3 --skill music-caption-rewriter
+```
+
+## Limitations
+
+- Inference requires CUDA.
+- Only non-streaming generation is currently supported.
+- The tokenized text prompt is limited to 5,000 tokens.
+- Audio generation is limited to 9,000 acoustic frames.
+- Section tags and music descriptions provide generative control rather than strict symbolic guarantees. The generated tempo, key, instrumentation, lyrics, and song structure may not always match every requested detail exactly.
+
+## Contact Us
+
+Contact us at [model@minimax.io](mailto:model@minimax.io).

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modular_model_index.json

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qwen_7B/qwen3-8B-tokenizer-music/added_tokens.json

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qwen_7B/qwen3-8B-tokenizer-music/special_tokens_map.json

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+{
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+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|audio_cfg|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

qwen_7B/qwen3-8B-tokenizer-music/tokenizer.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:bc63169ebf49c476995ced3f3dbae68f93ed9cf2a2997d3658863672f2f05f0f
+size 11423806

qwen_7B/qwen3-8B-tokenizer-music/tokenizer_config.json

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+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
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+      "content": "<|im_end|>",
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+      "rstrip": false,
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+      "special": true
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+      "content": "<|object_ref_end|>",
+      "lstrip": false,
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+      "rstrip": false,
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+      "special": true
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+      "lstrip": false,
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+      "single_word": false,
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+    "151658": {
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+      "special": false
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+      "lstrip": false,
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+      "content": "<|audio_end|>",
+      "lstrip": false,
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+      "lstrip": false,
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+      "content": "<|lyrics_start|>",
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+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
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+    "<|audio_cfg|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
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+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {{- messages[0].content + '\\n\\n' }}\n    {%- endif %}\n    {{- \"# 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>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\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\" }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n    {%- set index = (messages|length - 1) - loop.index0 %}\n    {%- 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>')) %}\n        {%- set ns.multi_step_tool = false %}\n        {%- set ns.last_query_index = index %}\n    {%- endif %}\n{%- endfor %}\n{%- for message in messages %}\n    {%- if message.content is string %}\n        {%- set content = message.content %}\n    {%- else %}\n        {%- set content = '' %}\n    {%- endif %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n        {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {%- set reasoning_content = '' %}\n        {%- if message.reasoning_content is string %}\n            {%- set reasoning_content = message.reasoning_content %}\n        {%- else %}\n            {%- if '</think>' in content %}\n                {%- set reasoning_content = content.split('</think>')[0].rstrip('\\n').split('<think>')[-1].lstrip('\\n') %}\n                {%- set content = content.split('</think>')[-1].lstrip('\\n') %}\n            {%- endif %}\n        {%- endif %}\n        {%- if loop.index0 > ns.last_query_index %}\n            {%- if loop.last or (not loop.last and reasoning_content) %}\n                {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content.strip('\\n') + '\\n</think>\\n\\n' + content.lstrip('\\n') }}\n            {%- else %}\n                {{- '<|im_start|>' + message.role + '\\n' + content }}\n            {%- endif %}\n        {%- else %}\n            {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- endif %}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n    {%- if enable_thinking is defined and enable_thinking is false %}\n        {{- '<think>\\n\\n</think>\\n\\n' }}\n    {%- endif %}\n{%- endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "model_max_length": 131072,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}

qwen_7B/qwen_7B/config.json

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+  "auto_map": {
+    "AutoConfig": "configuration_abab.AbabConfig",
+    "AutoModelForCausalLM": "modeling_abab.AbabForCausalLM"
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+  "model_type": "mixtral",
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+  "num_key_value_heads": 8,
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+  "output_router_logits": false,
+  "rms_norm_eps": 1e-06,
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+  "rotary_dim": 128,
+  "router_aux_loss_coef": 0.001,
+  "router_jitter_noise": 0.0,
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+  "tie_word_embeddings": false,
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