From a911dc26405b999aae8078eb5afb92bc06fb22e2 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Sat, 5 Sep 2026 22:27:12 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: MegaScience/Qwen3-8B-MegaScience Source: Original Platform --- .gitattributes | 51 ++++ README.md | 105 ++++++++ added_tokens.json | 28 +++ chat_template.jinja | 85 +++++++ config.json | 30 +++ configuration.json | 1 + generation_config.json | 6 + merges.txt | 3 + model-00001-of-00007.safetensors | 3 + model-00002-of-00007.safetensors | 3 + model-00003-of-00007.safetensors | 3 + model-00004-of-00007.safetensors | 3 + model-00005-of-00007.safetensors | 3 + model-00006-of-00007.safetensors | 3 + model-00007-of-00007.safetensors | 3 + model.safetensors.index.json | 406 +++++++++++++++++++++++++++++++ special_tokens_map.json | 31 +++ tokenizer.json | 3 + tokenizer_config.json | 240 ++++++++++++++++++ vocab.json | 3 + 20 files changed, 1013 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 added_tokens.json create mode 100644 chat_template.jinja create mode 100644 config.json create mode 100644 configuration.json create mode 100644 generation_config.json create mode 100644 merges.txt create mode 100644 model-00001-of-00007.safetensors create mode 100644 model-00002-of-00007.safetensors create mode 100644 model-00003-of-00007.safetensors create mode 100644 model-00004-of-00007.safetensors create mode 100644 model-00005-of-00007.safetensors create mode 100644 model-00006-of-00007.safetensors create mode 100644 model-00007-of-00007.safetensors create mode 100644 model.safetensors.index.json create mode 100644 special_tokens_map.json create mode 100644 tokenizer.json create mode 100644 tokenizer_config.json 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filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text + +merges.txt filter=lfs diff=lfs merge=lfs -text +tokenizer.json filter=lfs diff=lfs merge=lfs -text +vocab.json filter=lfs diff=lfs merge=lfs -text \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 0000000..4a5b345 --- /dev/null +++ b/README.md @@ -0,0 +1,105 @@ +--- +base_model: +- Qwen/Qwen3-8B-Base +datasets: +- MegaScience/MegaScience +language: +- en +license: apache-2.0 +metrics: +- accuracy +pipeline_tag: text-generation +library_name: transformers +tags: +- qwen +- science +- scientific-reasoning +- causal-lm +- instruction-tuning +--- + +# [MegaScience: Pushing the Frontiers of Post-Training Datasets for Science Reasoning](https://arxiv.org/abs/2507.16812) + +This repository hosts the **Qwen3-8B-MegaScience** model, a key component of the research presented in the paper "MegaScience: Pushing the Frontiers of Post-Training Datasets for Science Reasoning". + +## Abstract +Scientific reasoning is critical for developing AI scientists and supporting human researchers in advancing the frontiers of natural science discovery. However, the open-source community has primarily focused on mathematics and coding while neglecting the scientific domain, largely due to the absence of open, large-scale, high-quality, verifiable scientific reasoning datasets. To bridge this gap, we first present TextbookReasoning, an open dataset featuring truthful reference answers extracted from 12k university-level scientific textbooks, comprising 650k reasoning questions spanning 7 scientific disciplines. We further introduce MegaScience, a large-scale mixture of high-quality open-source datasets totaling 1.25 million instances, developed through systematic ablation studies that evaluate various data selection methodologies to identify the optimal subset for each publicly available scientific dataset. Meanwhile, we build a comprehensive evaluation system covering diverse subjects and question types across 15 benchmarks, incorporating comprehensive answer extraction strategies to ensure accurate evaluation metrics. Our experiments demonstrate that our datasets achieve superior performance and training efficiency with more concise response lengths compared to existing open-source scientific datasets. Furthermore, we train Llama3.1, Qwen2.5, and Qwen3 series base models on MegaScience, which significantly outperform the corresponding official instruct models in average performance. In addition, MegaScience exhibits greater effectiveness for larger and stronger models, suggesting a scaling benefit for scientific tuning. We release our data curation pipeline, evaluation system, datasets, and seven trained models to the community to advance scientific reasoning research. + +## Code +The official implementation and full codebase are available on the [MegaScience GitHub repository](https://github.com/GAIR-NLP/lm-open-science-evaluation). + +## Qwen3-8B-MegaScience + +### Training Recipe + +- **LR**: 5e-6 +- **LR Schedule**: Cosine +- **Batch Size**: 512 +- **Max Length**: 4,096 +- **Warm Up Ratio**: 0.05 +- **Epochs**: 3 + +### Usage + +You can load the model and tokenizer using the `transformers` library and perform text generation. For Qwen models, it is often recommended to use the `apply_chat_template` method for instruction-following tasks. + +```python +from transformers import AutoModelForCausalLM, AutoTokenizer +import torch + +model_id = "MegaScience/Qwen3-8B-MegaScience" + +# Load model with bfloat16 for better performance on compatible GPUs +# or use torch.float16 if bfloat16 is not supported +model = AutoModelForCausalLM.from_pretrained( + model_id, + torch_dtype=torch.bfloat16, + device_map="auto" # Automatically maps model to available devices (e.g., GPU) +) +tokenizer = AutoTokenizer.from_pretrained(model_id) + +# Example for chat completion +messages = [ + {"role": "user", "content": "Explain Newton's first law of motion in simple terms."}, +] + +input_ids = tokenizer.apply_chat_template( + messages, + tokenize=True, + add_generation_prompt=True, # Important for instruction-tuned models + return_tensors="pt" +).to(model.device) + +outputs = model.generate(input_ids, max_new_tokens=256, do_sample=True, temperature=0.7) +print(tokenizer.decode(outputs[0], skip_special_tokens=True)) +``` + +### Evaluation Results + +
+Data Pipeline +
+ +
+Data Pipeline +
+ +### More about MegaScience + +
+Data Pipeline +
+ +## Citation + +Check out our [paper](https://arxiv.org/abs/2507.16812) for more details. If you use our dataset or find our work useful, please cite + +``` +@article{fan2025megascience, + title={MegaScience: Pushing the Frontiers of Post-Training Datasets for Science Reasoning}, + author={Fan, Run-Ze and Wang, Zengzhi and Liu, Pengfei}, + year={2025}, + journal={arXiv preprint arXiv:2507.16812}, + url={https://arxiv.org/abs/2507.16812} +} +``` \ No newline at end of file diff --git a/added_tokens.json b/added_tokens.json new file mode 100644 index 0000000..b54f913 --- /dev/null +++ b/added_tokens.json @@ -0,0 +1,28 @@ +{ + "": 151668, + "": 151658, + "": 151666, + "": 151667, + "": 151657, + "": 151665, + "<|box_end|>": 151649, + "<|box_start|>": 151648, + "<|endoftext|>": 151643, + "<|file_sep|>": 151664, + "<|fim_middle|>": 151660, + "<|fim_pad|>": 151662, + "<|fim_prefix|>": 151659, + "<|fim_suffix|>": 151661, + "<|im_end|>": 151645, + "<|im_start|>": 151644, + "<|image_pad|>": 151655, + "<|object_ref_end|>": 151647, + "<|object_ref_start|>": 151646, + "<|quad_end|>": 151651, + "<|quad_start|>": 151650, + "<|repo_name|>": 151663, + "<|video_pad|>": 151656, + "<|vision_end|>": 151653, + "<|vision_pad|>": 151654, + "<|vision_start|>": 151652 +} diff --git a/chat_template.jinja b/chat_template.jinja new file mode 100644 index 0000000..699ff8d --- /dev/null +++ b/chat_template.jinja @@ -0,0 +1,85 @@ +{%- 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 XML tags:\n" }} + {%- for tool in tools %} + {{- "\n" }} + {{- tool | tojson }} + {%- endfor %} + {{- "\n\n\nFor each function call, return a json object with function name and arguments within XML tags:\n\n{\"name\": , \"arguments\": }\n<|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 not(message.content.startswith('') and message.content.endswith('')) %} + {%- set ns.multi_step_tool = false %} + {%- set ns.last_query_index = index %} + {%- endif %} +{%- endfor %} +{%- for message in messages %} + {%- if (message.role == "user") or (message.role == "system" and not loop.first) %} + {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }} + {%- elif message.role == "assistant" %} + {%- set content = message.content %} + {%- set reasoning_content = '' %} + {%- if message.reasoning_content is defined and message.reasoning_content is not none %} + {%- set reasoning_content = message.reasoning_content %} + {%- else %} + {%- if '' in message.content %} + {%- set content = message.content.split('')[-1].lstrip('\n') %} + {%- set reasoning_content = message.content.split('')[0].rstrip('\n').split('')[-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\n' + reasoning_content.strip('\n') + '\n\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 %} + {{- '\n{"name": "' }} + {{- tool_call.name }} + {{- '", "arguments": ' }} + {%- if tool_call.arguments is string %} + {{- tool_call.arguments }} + {%- else %} + {{- tool_call.arguments | tojson }} + {%- endif %} + {{- '}\n' }} + {%- endfor %} + {%- endif %} + {{- '<|im_end|>\n' }} + {%- elif message.role == "tool" %} + {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %} + {{- '<|im_start|>user' }} + {%- endif %} + {{- '\n\n' }} + {{- message.content }} + {{- '\n' }} + {%- 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 %} + {{- '\n\n\n\n' }} + {%- endif %} +{%- endif %} \ No newline at end of file diff --git a/config.json b/config.json new file mode 100644 index 0000000..72621cb --- /dev/null +++ b/config.json @@ -0,0 +1,30 @@ +{ + "architectures": [ + "Qwen3ForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": 151643, + "eos_token_id": 151643, + "head_dim": 128, + "hidden_act": 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