File size: 4,235 Bytes
e2d8213 7d49dc9 e2d8213 9024fe8 7d49dc9 e2d8213 7d49dc9 e2d8213 7d49dc9 e2d8213 7d49dc9 e2d8213 7d49dc9 e2d8213 7d49dc9 e2d8213 7d49dc9 e2d8213 7d49dc9 e2d8213 7d49dc9 e2d8213 7d49dc9 25531a8 7d49dc9 e2d8213 7d49dc9 e2d8213 7d49dc9 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 |
---
base_model:
- Menlo/Jan-nano
- POLARIS-Project/Polaris-4B-Preview
- Qwen/Qwen3-4B
library_name: transformers
tags:
- mergekit
- merge
---
# Qwen3-4B-Agentic-Reasoner
<img src="modelcard.png" widhth="400"/>
`yasserrmd/qwen3-4b-agentic-reasoner` is a merged model that combines the **agentic instruction-following strength** of [Menlo/Jan-nano](https://huggingface.co/Menlo/Jan-nano) with the **reasoning and structured thought capabilities** of [POLARIS-Project/Polaris-4B-Preview](https://huggingface.co/POLARIS-Project/Polaris-4B-Preview), using the [Qwen/Qwen3-4B](https://huggingface.co/Qwen/Qwen3-4B) architecture as the base.
This merge was performed using [mergekit](https://github.com/cg123/mergekit) and the [TIES](https://arxiv.org/abs/2306.01708) method for fine-grained parameter blending.
---
## 🧠 Intended Use
This model is intended for use in:
- Multi-step reasoning tasks
- Agent-style instruction following (CLI assistants, web automation)
- Educational assistance, planning, and explanation
- Natural language code generation, JSON/schema design
- Legal, productivity, and roleplay simulations
---
## 🧪 Merge Details
### 🔀 Merge Method
This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) merge method with the [Qwen/Qwen3-4B](https://huggingface.co/Qwen/Qwen3-4B) as the base model.
### 🤝 Models Merged
| Model | Role |
|-------|------|
| [POLARIS-Project/Polaris-4B-Preview](https://huggingface.co/POLARIS-Project/Polaris-4B-Preview) | Deep reasoning & CoT |
| [Menlo/Jan-nano](https://huggingface.co/Menlo/Jan-nano) | Agentic & Instruction-following |
### ⚙️ Configuration
```yaml
models:
- model: POLARIS-Project/Polaris-4B-Preview
parameters:
weight: 0.5
- model: Menlo/Jan-nano
parameters:
weight: 0.5
merge_method: ties
base_model: Qwen/Qwen3-4B
parameters:
normalize: true
int8_mask: true
dtype: float16
````
---
## 📊 Prompt Evaluation
This model was evaluated on **handcrafted prompts** covering:
* Chain-of-thought reasoning
* Math and logic
* Code writing and CLI instructions
* JSON/schema generation
* Role-based planning and writing tasks
* Arabic translation
* Legal drafting
### ✅ Performance Highlights
| Criterion | Result |
| -------------------------- | --------------------------------------- |
| CoT Reasoning | Excellent (multi-step math, planning) |
| Agentic Tasks | Strong (shell scripts, terminal agents) |
| Code Output | Clean formatting and logical structure |
| Format Awareness | Recognizes JSON, email, legal structure |
| Instruction Follow-through | Reliable and contextual |
| Language Tasks | Accurate Arabic translation, paraphrase |
Average prompt score (0–3 scale): **2.15**
All outputs were logical, well-structured, and contextually accurate for the prompt types.
---
## 🚀 Inference
To use the model:
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
model_id = "yasserrmd/qwen3-4b-agentic-reasoner"
tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto", device_map="auto", trust_remote_code=True)
prompt = "Plan the first 3 steps for launching a nonprofit AI education platform."
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```
---
## ⚠️ License & Use
Respect the licenses of the original merged models. This model is released for **research and personal experimentation** purposes.
* [POLARIS-Project/Polaris-4B-Preview License](https://huggingface.co/POLARIS-Project/Polaris-4B-Preview)
* [Menlo/Jan-nano License](https://huggingface.co/Menlo/Jan-nano)
* [Qwen3-4B License](https://huggingface.co/Qwen/Qwen3-4B)
---
## 🙏 Acknowledgments
Thanks to the teams behind:
* Alibaba's Qwen3 series
* Menlo/Jan-nano project
* POLARIS RL framework
* MergeKit by [@cg123](https://github.com/cg123)
---
Model by [@yasserrmd](https://huggingface.co/yasserrmd)
|