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qwen3_5_9b_base/hf_checkpoint/README.md DELETED
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- ---
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- library_name: transformers
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- license: apache-2.0
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- license_link: https://huggingface.co/Qwen/Qwen3.5-9B-Base/blob/main/LICENSE
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- pipeline_tag: image-text-to-text
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- ---
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-
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- # Qwen3.5-9B-Base
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-
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- <img width="400px" src="https://qianwen-res.oss-accelerate.aliyuncs.com/logo_qwen3.5.png">
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-
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- [![Qwen Chat](https://img.shields.io/badge/%F0%9F%92%9C%EF%B8%8F%20Qwen%20Chat%20-536af5)](https://chat.qwen.ai)
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-
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- > [!Note]
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- > This repository contains model weights and configuration files for the pre-trained only model in the Hugging Face Transformers format.
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- >
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- > These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, etc.
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- >
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- > The intended use cases are fine-tuning, in-context learning experiments, and other research or development purposes, not direct interaction.
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- > However, the control tokens, e.g., `<|im_start|>` and `<|im_end|>` were trained to allow efficient LoRA-style PEFT with the official chat template, mitigating the need to finetune embeddings, a significant optimization given Qwen3.5's larger vocabulary.
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-
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-
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- Over recent months, we have intensified our focus on developing foundation models that deliver exceptional utility and performance. Qwen3.5 represents a significant leap forward, integrating breakthroughs in multimodal learning, architectural efficiency, reinforcement learning scale, and global accessibility to empower developers and enterprises with unprecedented capability and efficiency.
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-
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- ## Qwen3.5 Highlights
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-
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- Qwen3.5 features the following enhancement:
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-
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- - **Unified Vision-Language Foundation**: Early fusion training on multimodal tokens achieves cross-generational parity with Qwen3 and outperforms Qwen3-VL models across reasoning, coding, agents, and visual understanding benchmarks.
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-
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- - **Efficient Hybrid Architecture**: Gated Delta Networks combined with sparse Mixture-of-Experts deliver high-throughput inference with minimal latency and cost overhead.
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-
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- - **Scalable RL Generalization**: Reinforcement learning scaled across million-agent environments with progressively complex task distributions for robust real-world adaptability.
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-
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- - **Global Linguistic Coverage**: Expanded support to 201 languages and dialects, enabling inclusive, worldwide deployment with nuanced cultural and regional understanding.
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-
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- - **Next-Generation Training Infrastructure**: Near-100% multimodal training efficiency compared to text-only training and asynchronous RL frameworks supporting massive-scale agent scaffolds and environment orchestration.
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-
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-
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- For more details, please refer to our blog post [Qwen3.5](https://qwen.ai/blog?id=qwen3.5).
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-
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-
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- ## Model Overview
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-
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- - Type: Causal Language Model with Vision Encoder
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- - Training Stage: Pre-training & Post-training
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- - Language Model
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- - Number of Parameters: 9B
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- - Hidden Dimension: 4096
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- - Token Embedding: 248320 (Padded)
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- - Number of Layers: 32
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- - Hidden Layout: 8 × (3 × (Gated DeltaNet → FFN) → 1 × (Gated Attention → FFN))
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- - Gated DeltaNet:
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- - Number of Linear Attention Heads: 32 for V and 16 for QK
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- - Head Dimension: 128
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- - Gated Attention:
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- - Number of Attention Heads: 16 for Q and 4 for KV
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- - Head Dimension: 256
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- - Rotary Position Embedding Dimension: 64
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- - Feed Forward Network:
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- - Intermediate Dimension: 12288
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- - LM Output: 248320 (Padded)
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- - MTP: trained with multi-steps
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- - Context Length: 262,144 natively and extensible up to 1,010,000 tokens.
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-
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- ### Citation
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-
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- If you find our work helpful, feel free to give us a cite.
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-
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- ```bibtex
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- @misc{qwen3.5,
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- title = {{Qwen3.5}: Towards Native Multimodal Agents},
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- author = {{Qwen Team}},
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- month = {February},
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- year = {2026},
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- url = {https://qwen.ai/blog?id=qwen3.5}
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- }
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- ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
qwen3_5_9b_base/hf_checkpoint/config.json DELETED
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- {
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- "architectures": [
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- "Qwen3_5ForConditionalGeneration"
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- ],
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- "image_token_id": 248056,
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- "model_type": "qwen3_5",
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- "text_config": {
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- "attention_bias": false,
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- "attention_dropout": 0.0,
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- "attn_output_gate": true,
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- "dtype": "bfloat16",
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- "eos_token_id": 248046,
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- "full_attention_interval": 4,
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- "head_dim": 256,
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- "hidden_act": "silu",
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- "hidden_size": 4096,
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- "initializer_range": 0.02,
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- "intermediate_size": 12288,
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- "layer_types": [
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- "linear_attention",
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- "linear_attention",
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- "linear_attention",
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- "full_attention",
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- "linear_attention",
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- "linear_attention",
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- "linear_attention",
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- "full_attention",
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- "linear_attention",
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- "linear_attention",
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- "linear_attention",
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- "full_attention",
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- "linear_attention",
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- "linear_attention",
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- "linear_attention",
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- "full_attention",
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- "linear_attention",
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- "linear_attention",
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- "linear_attention",
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- "full_attention",
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- "linear_attention",
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- "linear_attention",
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- "linear_attention",
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- "full_attention",
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- "linear_attention",
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- "linear_attention",
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- "linear_attention",
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- "full_attention",
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- "linear_attention",
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- "linear_attention",
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- "linear_attention",
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- "full_attention"
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- ],
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- "linear_conv_kernel_dim": 4,
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- "linear_key_head_dim": 128,
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- "linear_num_key_heads": 16,
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- "linear_num_value_heads": 32,
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- "linear_value_head_dim": 128,
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- "max_position_embeddings": 262144,
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- "mlp_only_layers": [],
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- "model_type": "qwen3_5_text",
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- "mtp_num_hidden_layers": 1,
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- "mtp_use_dedicated_embeddings": false,
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- "num_attention_heads": 16,
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- "num_hidden_layers": 32,
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- "num_key_value_heads": 4,
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- "rms_norm_eps": 1e-06,
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- "use_cache": true,
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- "vocab_size": 248320,
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- "mamba_ssm_dtype": "float32",
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- "rope_parameters": {
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- "mrope_interleaved": true,
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- "mrope_section": [
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- 11,
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- 11,
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- 10
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- ],
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- "rope_type": "default",
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- "rope_theta": 10000000,
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- "partial_rotary_factor": 0.25
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- },
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- "pad_token_id": 248044
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- },
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- "tie_word_embeddings": false,
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- "transformers_version": "4.57.0.dev0",
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- "video_token_id": 248057,
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- "vision_config": {
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- "deepstack_visual_indexes": [],
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- "depth": 27,
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- "hidden_act": "gelu_pytorch_tanh",
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- "hidden_size": 1152,
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- "in_channels": 3,
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- "initializer_range": 0.02,
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- "intermediate_size": 4304,
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- "model_type": "qwen3_5",
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- "num_heads": 16,
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- "num_position_embeddings": 2304,
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- "out_hidden_size": 4096,
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- "patch_size": 16,
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- "spatial_merge_size": 2,
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- "temporal_patch_size": 2
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- },
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- "vision_end_token_id": 248054,
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- "vision_start_token_id": 248053,
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- "eos_token_id": 248046,
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- "pad_token_id": 248044
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- }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- "chat_template": "{%- set image_count = namespace(value=0) %}\n{%- set video_count = namespace(value=0) %}\n{%- macro render_content(content, do_vision_count, is_system_content=false) %}\n {%- if content is string %}\n {{- content }}\n {%- elif content is iterable and content is not mapping %}\n {%- for item in content %}\n {%- if 'image' in item or 'image_url' in item or item.type == 'image' %}\n {%- if is_system_content %}\n {{- raise_exception('System message cannot contain images.') }}\n {%- endif %}\n {%- if do_vision_count %}\n {%- set image_count.value = image_count.value + 1 %}\n {%- endif %}\n {%- if add_vision_id %}\n {{- 'Picture ' ~ image_count.value ~ ': ' }}\n {%- endif %}\n {{- '<|vision_start|><|image_pad|><|vision_end|>' }}\n {%- elif 'video' in item or item.type == 'video' %}\n {%- if is_system_content %}\n {{- raise_exception('System message cannot contain videos.') }}\n {%- endif %}\n {%- if do_vision_count %}\n {%- set video_count.value = video_count.value + 1 %}\n {%- endif %}\n {%- if add_vision_id %}\n {{- 'Video ' ~ video_count.value ~ ': ' }}\n {%- endif %}\n {{- '<|vision_start|><|video_pad|><|vision_end|>' }}\n {%- elif 'text' in item %}\n {{- item.text }}\n {%- else %}\n {{- raise_exception('Unexpected item type in content.') }}\n {%- endif %}\n {%- endfor %}\n {%- elif content is none or content is undefined %}\n {{- '' }}\n {%- else %}\n {{- raise_exception('Unexpected content type.') }}\n {%- endif %}\n{%- endmacro %}\n{%- if not messages %}\n {{- raise_exception('No messages provided.') }}\n{%- endif %}\n{%- if tools and tools is iterable and tools is not mapping %}\n {{- '<|im_start|>system\\n' }}\n {{- \"# Tools\\n\\nYou have access to the following functions:\\n\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\" }}\n {{- '\\n\\nIf you choose to call a function ONLY reply in the following format with NO suffix:\\n\\n<tool_call>\\n<function=example_function_name>\\n<parameter=example_parameter_1>\\nvalue_1\\n</parameter>\\n<parameter=example_parameter_2>\\nThis is the value for the second parameter\\nthat can span\\nmultiple lines\\n</parameter>\\n</function>\\n</tool_call>\\n\\n<IMPORTANT>\\nReminder:\\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\\n- Required parameters MUST be specified\\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\\n</IMPORTANT>' }}\n {%- if messages[0].role == 'system' %}\n {%- set content = render_content(messages[0].content, false, true)|trim %}\n {%- if content %}\n {{- '\\n\\n' + content }}\n {%- endif %}\n {%- endif %}\n {{- '<|im_end|>\\n' }}\n{%- else %}\n {%- if messages[0].role == 'system' %}\n {%- set content = render_content(messages[0].content, false, true)|trim %}\n {{- '<|im_start|>system\\n' + 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\" %}\n {%- set content = render_content(message.content, false)|trim %}\n {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}\n {%- set ns.multi_step_tool = false %}\n {%- set ns.last_query_index = index %}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if ns.multi_step_tool %}\n {{- raise_exception('No user query found in messages.') }}\n{%- endif %}\n{%- for message in messages %}\n {%- set content = render_content(message.content, true)|trim %}\n {%- if message.role == \"system\" %}\n {%- if not loop.first %}\n {{- raise_exception('System message must be at the beginning.') }}\n {%- endif %}\n {%- elif message.role == \"user\" %}\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 {%- set reasoning_content = reasoning_content|trim %}\n {%- if loop.index0 > ns.last_query_index %}\n {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content + '\\n</think>\\n\\n' + content }}\n {%- else %}\n {{- '<|im_start|>' + message.role + '\\n' + content }}\n {%- endif %}\n {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {%- if loop.first %}\n {%- if content|trim %}\n {{- '\\n\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n {%- else %}\n {{- '<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n {%- endif %}\n {%- else %}\n {{- '\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n {%- endif %}\n {%- if tool_call.arguments is defined %}\n {%- for args_name, args_value in tool_call.arguments|items %}\n {{- '<parameter=' + args_name + '>\\n' }}\n {%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}\n {{- args_value }}\n {{- '\\n</parameter>\\n' }}\n {%- endfor %}\n {%- endif %}\n {{- '</function>\\n</tool_call>' }}\n {%- endfor %}\n {%- endif %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if loop.previtem and loop.previtem.role != \"tool\" %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- content }}\n {{- '\\n</tool_response>' }}\n {%- if not loop.last and loop.nextitem.role != \"tool\" %}\n {{- '<|im_end|>\\n' }}\n {%- elif loop.last %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- else %}\n {{- raise_exception('Unexpected message role.') }}\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 {%- else %}\n {{- '<think>\\n' }}\n {%- endif %}\n{%- endif %}",
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- "extra_special_tokens": {
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- "audio_bos_token": "<|audio_start|>",
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- "audio_eos_token": "<|audio_end|>",
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- "audio_token": "<|audio_pad|>",
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- "image_token": "<|image_pad|>",
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- "video_token": "<|video_pad|>",
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- "vision_bos_token": "<|vision_start|>",
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- "vision_eos_token": "<|vision_end|>"
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- }
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- }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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