NYCU IAlI DL2026 LLM2 SFT With Reasoning Data
This repository contains the LoRA adapter trained for the NYCU-IAII-DL2026 LLM #2 task: Reasoning LLM SFT with Reasoning Information.
Model source
- Kind
- Other
- File size
- 114 MB
- Base model
- Qwen/Qwen2.5-7B-Instruct
- Version
- vRevision 5618660
- Updated
- Oct 21, 2026
- Publisher
- @You-En
- Downloads
- 12
- Parameters
- 7B
- Source
- Hugging Face
Source description
NYCU-IAII-DL2026 LLM2 SFT with Reasoning
This repository contains the LoRA adapter trained for the NYCU-IAII-DL2026 LLM #2 task:
Reasoning LLM SFT with Reasoning Information.
The adapter is fine-tuned from:
Qwen/Qwen2.5-7B-Instruct
This repository does not contain a full merged model. It contains a PEFT / LoRA adapter that should be loaded on top of the base model.
Model Details
- Base model: Qwen/Qwen2.5-7B-Instruct
- Fine-tuning method: Supervised fine-tuning with reasoning information
- Adapter method: LoRA / PEFT
- Quantization during training: 4-bit quantization
- Framework: PyTorch, Transformers, PEFT
- Task type: Multiple-choice question answering with reasoning information
- Expected output: one of A, B, C, or D
Files
This repository includes:
adapter_config.json
adapter_model.safetensors
tokenizer.json
tokenizer_config.json
chat_template.jinja
README.md
Limitations
This adapter is trained specifically for the course multiple-choice reasoning task. It may not generalize well to open-ended reasoning or general chat scenarios.
Sources
1 source
Sources
1 sourceVerified Oct 21
Model artifacts
1 artifact
Model artifacts
1 artifactSource excerpts
3 excerpts
Source excerpts
3 excerpts--- language: - zh - en library_name: peft pipeline_tag: text-generation base_model: Qwen/Qwen2.5-7B-Instruct tags: - peft - lora - qwen2.5 - reasoning - supervised-finetuning - text-generation - nycu-iaii-dl2026 --- # NYCU-IAII-DL2026 LLM2 SFT with Reasoning This repository contains the **LoRA adapter** trained for the NYCU-IAII-DL2026 LLM #2 task: **Reasoning LLM SFT with Reasoning Information**. The adapter is fine-tuned from: ```text Qwen/Qwen2.5-7B-Instruct ``` This repository does not contain a full merged model. It contains a PEFT / LoRA adapter that should be loaded on top of the base model. ## Model Details - Base model: Qwen/Qwen2.5-7B-Instruct - Fine-tuning method: Supervised fine-tuning with reasoning information - Adapter method: LoRA / PEFT - Quantization during training: 4-bit quantization - Framework: PyTorch, Transformers, PEFT - Task type: Multiple-choice question answering with reasoning information - Expected output: one of A, B, C, or D ## Files This repository includes: ```text adapter_config.json adapter_model.safetensors tokenizer.json tokenizer_config.json chat_template.jinja README.md ``` ## Limitations This adapter is trained specifically for the course multiple-choice reasoning task. It may not generalize well to open-ended reasoning or general chat scenarios.
Source context: 12 downloads · 0 likes · Pipeline text-generation · Library peft · Repo You-En/NYCU_IAlI_DL2026_LLM2_SFT_with_Reasoning_Data
Source context: 19 downloads · 0 likes · Pipeline text-generation · Library peft · Repo You-En/NYCU_IAlI_DL2026_LLM2_SFT_with_Reasoning_Data
