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
File size: 503 Bytes
f7df3ab | 1 2 3 4 5 6 7 8 9 10 11 12 | {
"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"
}
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