Text Generation
PEFT
Safetensors
English
Turkish
qwen3
lora
research-reasoning
question-answering
evidence-grounded
structured-generation
json
rejection-sampling
reinforcement-learning
conversational
Instructions to use Ethosoft/Qwen3-1.7B-ResearchReasoning-JSON-RL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Ethosoft/Qwen3-1.7B-ResearchReasoning-JSON-RL with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-1.7B") model = PeftModel.from_pretrained(base_model, "Ethosoft/Qwen3-1.7B-ResearchReasoning-JSON-RL") - Notebooks
- Google Colab
- Kaggle
| { | |
| "repo_id": "Ethosoft/Qwen3-1.7B-ResearchReasoning-JSON-RL", | |
| "base_model": "Qwen/Qwen3-1.7B", | |
| "artifact_type": "PEFT LoRA adapter", | |
| "project_stage_name": "RL-lite", | |
| "method_note": "Verifier-guided rejection sampling followed by supervised fine-tuning; not full online policy-gradient RL.", | |
| "fine_tuning_max_sequence_length": 4096, | |
| "languages": ["en", "tr"], | |
| "github": "https://github.com/Ahmet2001/QA-research-SLM", | |
| "gguf_repo": "Ethosoft/Qwen3-1.7B-ResearchReasoning-JSON-RL-GGUF" | |
| } | |