Text Generation
PEFT
Safetensors
GGUF
English
Thai
lora
qwen3.5-moe
qwen3.6
reasoning
kimi-k2.6
claude-opus
distillation
weight-diff
svd
Instructions to use hotdogs/qwen3.6-35b-opus-to-kimi-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use hotdogs/qwen3.6-35b-opus-to-kimi-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("lordx64/Qwen3.6-35B-A3B-Claude-4.7-Opus-Reasoning-Distilled") model = PeftModel.from_pretrained(base_model, "hotdogs/qwen3.6-35b-opus-to-kimi-lora") - Notebooks
- Google Colab
- Kaggle
| \relax | |
| \providecommand\hyper@newdestlabel[2]{} | |
| \providecommand\HyField@AuxAddToFields[1]{} | |
| \providecommand\HyField@AuxAddToCoFields[2]{} | |
| \citation{hu2021lora} | |
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| \newlabel{eq:lora_b}{{6}{2}{Truncated SVD Compression}{equation.2.6}{}} | |
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| \citation{shen2024moe} | |
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| \bibstyle{unsrt} | |
| \bibcite{hu2021lora}{1} | |
| \bibcite{dettmers2023qlora}{2} | |
| \bibcite{rombach2022ldm}{3} | |
| \bibcite{qwen2025}{4} | |
| \bibcite{shen2024moe}{5} | |
| \bibcite{dettmers2022optimizer}{6} | |
| \bibcite{mangrulkar2022peft}{7} | |
| \bibcite{unsloth2024}{8} | |
| \bibcite{moonshot2025}{9} | |
| \bibcite{anthropic2026}{10} | |
| \bibcite{nous2026hermes}{11} | |
| \bibcite{lordx64_2026}{12} | |
| \bibcite{bas95_2026}{13} | |
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