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Model: PokeeAI/pokee_research_7b Source: Original Platform
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README.md
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README.md
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---
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base_model:
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- Qwen/Qwen2.5-7B-Instruct
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datasets:
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- miromind-ai/MiroRL-GenQA
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language:
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- en
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license: apache-2.0
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tags:
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- agent
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- deepresearch
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- llm
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- rl
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- reinforcementlearning
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pipeline_tag: text-generation
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library_name: transformers
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---
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# Model Card for PokeeResearch
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## Model Details
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### Model Description
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**PokeeResearch-7B** is a **7-billion-parameter deep research agent** developed by **Pokee AI** to advance reliable, aligned, and scalable research-grade reasoning in tool-augmented LLMs.
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The model integrates **Reinforcement Learning from AI Feedback (RLAIF)** with a **robust reasoning scaffold**, enabling it to conduct complex, multi-step research workflows that include self-correction, verification, and synthesis across multiple independent research threads.
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- **Developed by:** Pokee AI
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- **Model type:** Tool-augmented large language model (LLM) research agent
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- **Language(s):** English, Chinese and many more
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- **License:** Apache 2.0
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- **Finetuned from model:** Qwen2.5-7B-Instruct
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### Model Sources
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- **Repository:** [https://github.com/Pokee-AI/PokeeResearchOSS](https://github.com/Pokee-AI/PokeeResearchOSS)
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- **Paper:** [*PokeeResearch: Effective Deep Research via Reinforcement Learning from AI Feedback and Robust Reasoning Scaffold*](https://arxiv.org/pdf/2510.15862), Pokee AI, October 2025
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- **Project Page:** [https://pokee.ai/deepresearch-preview](https://pokee.ai/deepresearch-preview)
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---
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## Uses
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### Direct Use
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PokeeResearch-7B is designed for **deep research automation**, where the model autonomously:
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- Decomposes complex user queries
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- Retrieves and reads from external sources
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- Synthesizes factual, verifiable, and grounded answers
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It can be used as a **standalone research assistant** or integrated into **multi-agent systems** to support academic, enterprise, or product-level research tasks.
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### Downstream Use
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PokeeResearch-7B can be **fine-tuned** or **extended** for:
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- Domain-specific scientific discovery
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- Autonomous document retrieval and synthesis
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- Multi-source verification and summarization pipelines
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- Integration into reinforcement learning research agents (RLHF/RLAIF frameworks)
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### Out-of-Scope Use
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The model should **not** be used for:
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- Generating unverified or speculative claims
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- Automated decision-making in high-stakes domains (medical, legal, or financial)
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- Applications requiring strict factual precision without external verification
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- Generating content without citation or evidence tracing
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---
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## Bias, Risks, and Limitations
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PokeeResearch-7B is optimized for factual grounding and robustness, but limitations include:
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- Dependence on **external data quality** and **retrieval accuracy**
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- Potential **semantic bias** introduced by AI-based feedback signals
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- Limited coverage for **non-English** or **multi-modal** reasoning tasks
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- Risk of **hallucinated synthesis** when sources conflict or lack clarity
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### Recommendations
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Users should:
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- Cross-verify answers, especially in multi-hop reasoning cases
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- Monitor output for citation accuracy and alignment with source data
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- Refrain from using outputs as sole evidence in decision-critical contexts
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---
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||||
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## How to Get Started with the Model
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please refer to the following codebase for how to use PokeeResearch-7B
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https://github.com/Pokee-AI/PokeeResearchOSS/blob/main/README.md
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|
||||
---
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||||
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## Training Details
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||||
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### Training Data
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- **Dataset:** MiroRL-GenQA dataset (MiroMind AI, 2025)
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- **Data characteristics:** Complex, multi-turn question–answer pairs requiring multi-step reasoning
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- **Data filtering:** No benchmark data used for testing; the model was trained only on open-domain text Q&A samples
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### Training Procedure
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||||
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#### Preprocessing
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- Normalization and tokenization aligned with Qwen2.5 tokenizer
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- Structured prompt–response pairs in research/verification format (`<tool_call>`, `<answer>`, `<verification>`)
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#### Training Hyperparameters
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- **Algorithm:** RLOO (REINFORCE Leave-One-Out)
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- **Batch size:** 64
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- **Research threads per prompt:** 8
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- **Learning rate:** 3e-6
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- **Context limit:** 32,768 tokens
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- **Steps:** 140 fine-tuning iterations
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- **Regularization:** None (no entropy or KL regularization)
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- **Precision regime:** bf16 mixed precision
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#### Reward Design
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- Combined reward signal from:
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- **AI feedback** (semantic equivalence via external LLM judge)
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- **Format adherence reward** (ensures correct agent behavior)
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||||
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||||
#### Speeds, Sizes, Times
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- **Model size:** 7 billion parameters
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- **Training duration:** ~5 days on 8 × A100 80G GPUs
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- **Checkpoint size:** ~13 GB
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||||
|
||||
---
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## Evaluation
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### Testing Data, Factors & Metrics
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||||
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#### Testing Data
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||||
10 open-domain research and QA benchmarks:
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- NQ, TriviaQA, PopQA, HotpotQA, 2WikiMultiHopQA, Musique, Bamboogle, GAIA, BrowseComp, Humanity’s Last Exam
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#### Factors
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- Benchmarks differ by reasoning depth, retrieval dependence, and factual precision requirements.
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- Evaluations disaggregate by dataset difficulty and task type (single-hop vs multi-hop).
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#### Metrics
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||||
- Mean accuracy (mean@4 across independent research threads) based on
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### Results
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||||
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||||
**PokeeResearch-7B (RTS variant)** and **PokeeResearch-7B** outperforms all baselines at 7B scale across 10 benchmarks.
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||||
Highlights (mean@4 accuracy):
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||||
| **Method** | **HLE** | **GAIA** | **BrowseComp** | **BAMB** | **2WIKI** | **TQ** | **NQ** | **POPQA** | **MUSIQUE** | **HOTPOTQA** |
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||||
|-------------|----------|-----------|----------------|-----------|-----------|----------|----------|-------------|---------------|----------------|
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||||
| R1searcher | 5.4 | 8.3 | 1.0 | 63.2 | 61.4 | 77.2 | 59.6 | 51.8 | 35.8 | 62.4 |
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||||
| SearchR1 | 13.0 | 18.7 | 0.4 | 67.8 | 62.8 | 81.0 | 67.6 | 59.6 | 33.2 | 63.2 |
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||||
| ZeroSearch | 8.6 | 9.9 | 1.4 | 51.4 | 33.6 | 61.6 | 48.2 | 38.0 | 19.0 | 32.4 |
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||||
| ASearcher | 13.8 | 22.1 | 3.2 | 68.8 | 69.2 | 85.2 | 71.2 | 58.2 | 35.8 | 71.0 |
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||||
| DeepResearcher | 6.0 | 24.03 | 1.8 | 71.0 | 58.8 | 82.2 | 60.2 | 55.2 | 26.8 | 56.6 |
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||||
| **PR** | **15.2** | **36.9** | **5.4** | **74.5** | **74.0** | **91.3** | **75.1** | **59.8** | **39.8** | **71.2** |
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||||
| **PR+** | **17.6** | **41.3** | **8.4** | **75.0** | **75.0** | **91.8** | **75.0** | **60.0** | **41.4** | **71.6** |
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||||
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||||
#### Summary
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||||
PokeeResearch-7B variants achieves **state-of-the-art performance among 7B-scale open deep research agents**, validating RLAIF and reasoning scaffold design for robust, verifiable research workflows.
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||||
---
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||||
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## Technical Specifications
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||||
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||||
### Model Architecture and Objective
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||||
- **Base Architecture:** Transformer decoder (Qwen2.5-7B-Instruct backbone)
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||||
- **Objective:** Reinforcement learning with AI feedback to maximize semantic correctness and alignment with human-style reasoning
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||||
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||||
### Compute Infrastructure
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||||
#### Hardware
|
||||
- NVIDIA A100 80GB GPUs ×8 for training and x1 for inference
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||||
---
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||||
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||||
## Citation
|
||||
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||||
**BibTeX:**
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||||
```bibtex
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||||
@article{pokee2025deepresearch,
|
||||
title={PokeeResearch: Effective Deep Research via
|
||||
Reinforcement Learning from AI Feedback and Robust Reasoning Scaffold},
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||||
author={Yi Wan* and Jiuqi Wang* and Liam Li
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||||
and Jinsong Liu and Ruihao Zhu and Zheqing Zhu},
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||||
journal={Pokee AI Technical Report},
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||||
year={2025},
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||||
url={https://arxiv.org/pdf/2510.15862}
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||||
}
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||||
```
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||||
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||||
**APA:**
|
||||
Wan, Y., Wang, J., Li, L., Liu, J., Zhu, R., & Zhu, Z. (2025). *PokeeResearch: Effective Deep Research via Reinforcement Learning from AI Feedback and Robust Reasoning Scaffold.* Pokee AI.
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||||
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||||
---
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||||
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||||
## Glossary
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||||
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||||
- **RLAIF:** Reinforcement Learning from AI Feedback – optimization using LLM-based reward signals.
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- **RLOO:** REINFORCE Leave-One-Out – unbiased policy gradient variant for on-policy learning.
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- **RTS:** Research Threads Synthesis – synthesis of multiple independent reasoning threads at inference time.
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||||
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||||
---
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||||
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||||
## More Information
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||||
For technical details, visit: [https://github.com/Pokee-AI/PokeeResearchOSS](https://github.com/Pokee-AI/PokeeResearchOSS)
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||||
For inquiries, contact: hello@pokee.ai
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||||
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||||
---
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||||
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## Model Card Authors
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||||
**Yi Wan**, **Jiuqi Wang**, Liam Li, Jinsong Liu, Ruihao Zhu, and Zheqing Zhu — Pokee AI Research Team
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||||
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||||
## Model Card Contact
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||||
Pokee AI Team — hello@pokee.ai
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added_tokens.json
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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||||
{%- if messages[0]['role'] == 'system' %}
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||||
{{- messages[0]['content'] }}
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||||
{%- else %}
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||||
{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
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||||
{%- endif %}
|
||||
{{- "\n\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>" }}
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||||
{%- for tool in tools %}
|
||||
{{- "\n" }}
|
||||
{{- tool | tojson }}
|
||||
{%- endfor %}
|
||||
{{- "\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" }}
|
||||
{%- else %}
|
||||
{%- if messages[0]['role'] == 'system' %}
|
||||
{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
|
||||
{%- else %}
|
||||
{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- for message in messages %}
|
||||
{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
|
||||
{%- elif message.role == "assistant" %}
|
||||
{{- '<|im_start|>' + message.role }}
|
||||
{%- if message.content %}
|
||||
{{- '\n' + message.content }}
|
||||
{%- endif %}
|
||||
{%- for tool_call in message.tool_calls %}
|
||||
{%- if tool_call.function is defined %}
|
||||
{%- set tool_call = tool_call.function %}
|
||||
{%- endif %}
|
||||
{{- '\n<tool_call>\n{"name": "' }}
|
||||
{{- tool_call.name }}
|
||||
{{- '", "arguments": ' }}
|
||||
{{- tool_call.arguments | tojson }}
|
||||
{{- '}\n</tool_call>' }}
|
||||
{%- endfor %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- elif message.role == "tool" %}
|
||||
{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
|
||||
{{- '<|im_start|>user' }}
|
||||
{%- endif %}
|
||||
{{- '\n<tool_response>\n' }}
|
||||
{{- message.content }}
|
||||
{{- '\n</tool_response>' }}
|
||||
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- if add_generation_prompt %}
|
||||
{{- '<|im_start|>assistant\n' }}
|
||||
{%- endif %}
|
||||
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config.json
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config.json
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{
|
||||
"architectures": [
|
||||
"Qwen2ForCausalLM"
|
||||
],
|
||||
"attention_dropout": 0.0,
|
||||
"eos_token_id": 151645,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 3584,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 18944,
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||||
"layer_types": [
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention"
|
||||
],
|
||||
"max_position_embeddings": 32768,
|
||||
"max_window_layers": 28,
|
||||
"model_type": "qwen2",
|
||||
"num_attention_heads": 28,
|
||||
"num_hidden_layers": 28,
|
||||
"num_key_value_heads": 4,
|
||||
"pad_token_id": 151643,
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||||
"rms_norm_eps": 1e-06,
|
||||
"rope_scaling": null,
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||||
"rope_theta": 1000000.0,
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||||
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|
||||
"added_tokens_decoder": {
|
||||
"151643": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151644": {
|
||||
"content": "<|im_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151645": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151646": {
|
||||
"content": "<|object_ref_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151647": {
|
||||
"content": "<|object_ref_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151648": {
|
||||
"content": "<|box_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151649": {
|
||||
"content": "<|box_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151650": {
|
||||
"content": "<|quad_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151651": {
|
||||
"content": "<|quad_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151652": {
|
||||
"content": "<|vision_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151653": {
|
||||
"content": "<|vision_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151654": {
|
||||
"content": "<|vision_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151655": {
|
||||
"content": "<|image_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151656": {
|
||||
"content": "<|video_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151657": {
|
||||
"content": "<tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151658": {
|
||||
"content": "</tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151659": {
|
||||
"content": "<|fim_prefix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151660": {
|
||||
"content": "<|fim_middle|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151661": {
|
||||
"content": "<|fim_suffix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151662": {
|
||||
"content": "<|fim_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"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
|
||||
}
|
||||
BIN
vocab.json
(Stored with Git LFS)
Normal file
BIN
vocab.json
(Stored with Git LFS)
Normal file
Binary file not shown.
Reference in New Issue
Block a user