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README.md

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+---
+license: mit
+tags:
+- RLinf
+language:
+- en
+metrics:
+- accuracy
+base_model:
+- deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
+pipeline_tag: reinforcement-learning
+model-index:
+- name: RLinf-math-7B
+  results:
+  - task:
+      type: math             # Required. Example: automatic-speech-recognition
+    dataset:
+      type: aime_2024          # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
+      name: AIME24         # Required. A pretty name for the dataset. Example: Common Voice (French)
+    metrics:
+      - type: accuracy        # Required. Example: wer. Use metric id from https://hf.co/metrics
+        value: 68.328125      # Required. Example: 20.90
+  - task:
+      type: math             # Required. Example: automatic-speech-recognition
+    dataset:
+      type: aime_2025          # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
+      name: AIME25        # Required. A pretty name for the dataset. Example: Common Voice (French)
+    metrics:
+      - type: accuracy        # Required. Example: wer. Use metric id from https://hf.co/metrics
+        value: 52.19375      # Required. Example: 20.90
+  - task:
+      type: stem             # Required. Example: automatic-speech-recognition
+    dataset:
+      type: gpqa_diamond          # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
+      name: GPQA-diamond         # Required. A pretty name for the dataset. Example: Common Voice (French)
+    metrics:
+      - type: accuracy        # Required. Example: wer. Use metric id from https://hf.co/metrics
+        value: 48.178124999999994      # Required. Example: 20.90
+---
+
+<div align="center">
+  <img src="logo.svg" alt="RLinf-logo" width="500"/>
+</div>
+
+
+<div align="center">
+<!-- <a href="TODO"><img src="https://img.shields.io/badge/arXiv-Paper-red?logo=arxiv"></a> -->
+<!-- <a href="TODO"><img src="https://img.shields.io/badge/HuggingFace-yellow?logo=huggingface&logoColor=white" alt="Hugging Face"></a> -->
+<a href="https://github.com/RLinf/RLinf"><img src="https://img.shields.io/badge/Github-blue"></a>
+<a href="https://rlinf-docs.readthedocs.io"><img src="https://img.shields.io/badge/Documentation-Purple?color=8A2BE2&logo=readthedocs"></a>
+<!-- <a href="TODO"><img src="https://devin.ai/assets/deepwiki-badge.png" alt="Ask DeepWiki.com" style="height:20px;"></a>
+<a href="TODO"><img src="https://img.shields.io/badge/微信-green?logo=wechat&amp"></a> -->
+</div>
+
+<h1 align="center">RLinf: Reinforcement Learning Infrastructure for Agentic AI</h1>
+
+[RLinf](https://github.com/RLinf/RLinf) is a flexible and scalable open-source infrastructure designed for post-training foundation models (LLMs, VLMs, VLAs) via reinforcement learning. The 'inf' in RLinf stands for Infrastructure, highlighting its role as a robust backbone for next-generation training. It also stands for Infinite, symbolizing the system’s support for open-ended learning, continuous generalization, and limitless possibilities in intelligence development.
+
+
+<div align="center">
+  <img src="overview.png" alt="RLinf-overview" width="600"/>
+</div>
+
+## Model Description
+The RLinf-math series is trained on DeepSeek-R1-Distill-Qwen (1.5B and 7B variants), using the same base models and training datasets as AReaL. Training with RLinf yields performance better than AReaL.
+
+We adopt Group Relative Policy Optimization (GRPO) with token-level loss aggregation, focusing on mathematical reasoning and long chain-of-thought (CoT) tasks.
+
+## Evaluation and Results
+We trained and evaluated two models using RLinf:
+
+- RLinf-math-1.5B Model (based on DeepSeek-R1-Distill-Qwen-1.5B)
+  - Recommended sampling settings:  `temperature = 0.6`, `top_p = 0.95`
+
+- RLinf-math-7B Model (based on DeepSeek-R1-Distill-Qwen-7B)
+  - Recommended sampling settings:  `temperature = 1.0`, `top_p = 0.95`
+
+### Benchmark Results
+
+|                                          | AIME24 | AIME25 | GPQA-diamond |
+| ---------------------------------------- | ------ | ------ | ------------ |
+| [DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B)            | 28.33  | 24.90  | 27.45        |
+| [DeepScaleR-1.5B-Preview](https://huggingface.co/agentica-org/DeepScaleR-1.5B-Preview)            | 40.41  | 30.93  | 27.54        |
+| [AReaL-1.5B](https://huggingface.co/inclusionAI/AReaL-1.5B-Preview-Stage-3)        |  40.73  | 31.56  |  28.1        |
+| AReaL-1.5B-retrain*       |  44.42  | 34.27  |  33.81       |
+| [RLinf-math-1.5B](https://huggingface.co/RLinf/RLinf-math-1.5B)                          | **48.44**  | **35.63**  | **38.46**        |
+
+
+|                             | AIME24 | AIME25 | GPQA-diamond |
+| --------------------------- | ------ | ------ | ------------ |
+| [DeepSeek-R1-Distill-Qwen-7B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B) | 54.90  | 40.20  | 45.48        |
+| [AReaL-7B](https://huggingface.co/inclusionAI/AReaL-boba-RL-7B)                    | 62.82  | 47.29  | 46.54        |
+| [RLinf-math-7B](https://huggingface.co/RLinf/RLinf-math-7B)               | **68.33**  | **52.19**  | **48.18**        |
+
+\* We retrain the model using the default settings for 600 steps. 
+
+## How to Use
+Example with Hugging Face `transformers`:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "RLinf/RLinf-math-7B"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto")
+
+prompt = "Solve: If x^2 + 2x + 1 = 0, what is x?"
+
+inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+outputs = model.generate(
+    **inputs,
+    max_new_tokens=512,
+    temperature=1.0,   # recommended for 7B
+    top_p=0.95
+)
+
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## License
+This code repository and the model weights are licensed under the MIT License.

config.json

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+{
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "hidden_act": "silu",
+  "hidden_size": 3584,
+  "initializer_range": 0.02,
+  "intermediate_size": 18944,
+  "max_position_embeddings": 131072,
+  "max_window_layers": 28,
+  "model_type": "qwen2",
+  "num_attention_heads": 28,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 4,
+  "rms_norm_eps": 1e-06,
+  "rope_theta": 10000,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.44.0",
+  "use_cache": true,
+  "use_mrope": false,
+  "use_sliding_window": false,
+  "vocab_size": 152064
+}

configuration.json

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

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 151646,
+  "eos_token_id": 151643,
+  "do_sample": true,
+  "temperature": 0.6,
+  "top_p": 0.95,
+  "transformers_version": "4.39.3"
+}

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+  "unk_token": null,
+  "tokenizer_class": "LlamaTokenizerFast",
+  "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<｜User｜>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<｜Assistant｜><｜tool▁calls▁begin｜><｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{%- set ns.is_first = true -%}{%- else %}{{'\\n' + '<｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{{'<｜tool▁calls▁end｜><｜end▁of▁sentence｜>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<｜tool▁outputs▁end｜>' + message['content'] + '<｜end▁of▁sentence｜>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{% if '</think>' in content %}{% set content = content.split('</think>')[-1] %}{% endif %}{{'<｜Assistant｜>' + content + '<｜end▁of▁sentence｜>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<｜tool▁outputs▁begin｜><｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\\n<｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<｜tool▁outputs▁end｜>'}}{% endif %}{% if add_generation_prompt and not ns.is_tool %}{{'<｜Assistant｜>'}}{% endif %}"
+}