1.4 KiB
1.4 KiB
library_name, license, pretty_name, base_model, tags
| library_name | license | pretty_name | base_model | tags | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| transformers | apache-2.0 | Qwen3-1.7B GPT-OSS-20B Distilled |
|
|
Qwen3-1.7B-GPT-OSS-20B-Distilled
This model is a fine-tuned version of Qwen/Qwen3-1.7B, distilled from openai/gpt-oss-20b using LoRA and SFTTrainer.
Model Description
This is a student model created through knowledge distillation from a larger, more capable teacher model. The goal is to transfer the knowledge and capabilities of the openai/gpt-oss-20b (teacher) to a smaller, more efficient Qwen/Qwen3-1.7B (student) model.
Training Details
- Teacher Model: openai/gpt-oss-20b
- Dataset: Synthetic dataset of 1000 samples in Brazilian Portuguese generated by the teacher using random samples from dominguesm/alpaca-data-pt-br.
- LoRA Config: r=16, alpha=32, dropout=0.05
- Training Hyperparams: 3 epochs, learning rate=0.0002, batch size=2
Usage
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel
model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-1.7B", device_map="auto")
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-1.7B")
model = PeftModel.from_pretrained(model, "wandgibaut/qwen-1.7b-gpt-oss-20b-distilled")