初始化项目，由ModelHub XC社区提供模型

Model: PKU-Alignment/s1-m_7b_beta
Source: Original Platform

.gitattributes

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README.md

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+---
+language:
+- en
+license: cc-by-nc-4.0
+pipeline_tag: image-text-to-text
+tags:
+  - multimodal
+base_model:
+  - Qwen/Qwen2-VL-7B-Instruct
+---
+# S1-M-7B-Beta
+
+[🏠 Homepage](https://github.com/PKU-Alignment/s1-m) | [👍 Our Official Code Repo](https://github.com/PKU-Alignment/s1-m) | [🤗 S1-M Dataset (Beta)](https://huggingface.co/datasets/PKU-Alignment/s1-m_beta) 
+
+S1-M-7B-Beta used for developing the algorithm "Simple Test-time Scaling in Multimodal Reasoning". By fine-tuning the base model `Qwen/Qwen2-VL-7B-Instruct` on data with thinking tags `<think>` and `</think>`, the model acquired the `think first, then response` paradigm, allowing for experiments on "Test-time Scaling".
+
+**Note: The current model is a development version, not the final official version.**

added_tokens.json

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+}

chat_template.json

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+{
+  "chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n{% endif %}<|im_start|>{{ message['role'] }}\n{% if message['content'] is string %}{{ message['content'] }}<|im_end|>\n{% else %}{% for content in message['content'] %}{% if content['type'] == 'image' or 'image' in content or 'image_url' in content %}{% set image_count.value = image_count.value + 1 %}{% if add_vision_id %}Picture {{ image_count.value }}: {% endif %}<|vision_start|><|image_pad|><|vision_end|>{% elif content['type'] == 'video' or 'video' in content %}{% set video_count.value = video_count.value + 1 %}{% if add_vision_id %}Video {{ video_count.value }}: {% endif %}<|vision_start|><|video_pad|><|vision_end|>{% elif 'text' in content %}{{ content['text'] }}{% endif %}{% endfor %}<|im_end|>\n{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant\n{% endif %}"
+}

config.json

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+{
+  "_attn_implementation_autoset": true,
+  "architectures": [
+    "Qwen2VLForConditionalGeneration"
+  ],
+  "attention_dropout": 0.0,
+  "eos_token_id": 151645,
+  "hidden_act": "silu",
+  "hidden_size": 3584,
+  "image_token_id": 151655,
+  "initializer_range": 0.02,
+  "intermediate_size": 18944,
+  "max_position_embeddings": 32768,
+  "max_window_layers": 28,
+  "model_type": "qwen2_vl",
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+  "num_hidden_layers": 28,
+  "num_key_value_heads": 4,
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+  "rms_norm_eps": 1e-06,
+  "rope_scaling": {
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+    "type": "default"
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+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.49.0",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "video_token_id": 151656,
+  "vision_config": {
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+}

configuration.json

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+{"framework": "pytorch", "task": "image-text-to-text", "allow_remote": true}

preprocessor_config.json

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+{
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+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
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+    0.4578275,
+    0.40821073
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+  "image_processor_type": "Qwen2VLImageProcessor",
+  "image_std": [
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+    0.26130258,
+    0.27577711
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+  "max_pixels": 25088,
+  "merge_size": 2,
+  "min_pixels": 3136,
+  "patch_size": 14,
+  "processor_class": "Qwen2VLProcessor",
+  "resample": 3,
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+  "size": {
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+    "shortest_edge": 3136
+  },
+  "temporal_patch_size": 2
+}

pytorch_model.bin

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special_tokens_map.json

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tokenizer_config.json

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+    "<|image_pad|>",
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+  "chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n{% endif %}<|im_start|>{{ message['role'] }}\n{% if message['content'] is string %}{{ message['content'] }}<|im_end|>\n{% else %}{% for content in message['content'] %}{% if content['type'] == 'image' or 'image' in content or 'image_url' in content %}{% set image_count.value = image_count.value + 1 %}{% if add_vision_id %}Picture {{ image_count.value }}: {% endif %}<|vision_start|><|image_pad|><|vision_end|>{% elif content['type'] == 'video' or 'video' in content %}{% set video_count.value = video_count.value + 1 %}{% if add_vision_id %}Video {{ video_count.value }}: {% endif %}<|vision_start|><|video_pad|><|vision_end|>{% elif 'text' in content %}{{ content['text'] }}{% endif %}{% endfor %}<|im_end|>\n{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant\n{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "model_max_length": 32000,
+  "pad_token": "<|endoftext|>",
+  "padding_side": "right",
+  "processor_class": "Qwen2VLProcessor",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
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+}