Text Generation
PEFT
Safetensors
English
Russian
qwen
qwen3.5
lora
qlora
code
rag
instruction-following
translation
game-localization
conversational
Instructions to use taylonmcfly/Qwen3.5-9B-Existence-Code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use taylonmcfly/Qwen3.5-9B-Existence-Code with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/workspace/train/qwen35_diligent_lora/models/Qwen3.5-9B-Base") model = PeftModel.from_pretrained(base_model, "taylonmcfly/Qwen3.5-9B-Existence-Code") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 72b422f28617aba1c16c70b1a29cc8c6c51a630a398f5402e813f7704d7318b5
- Size of remote file:
- 20 MB
- SHA256:
- 06b9509352d2af50381ab2247e083b80d32d5c0aba91c272ca9ff729b6a0e523
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.