Instructions to use Pablo-Flores-Mollinedo/verilog-qwen2.5-coder-7b-v9-auto-distilled-direct-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Pablo-Flores-Mollinedo/verilog-qwen2.5-coder-7b-v9-auto-distilled-direct-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-Coder-7B-Instruct") model = PeftModel.from_pretrained(base_model, "Pablo-Flores-Mollinedo/verilog-qwen2.5-coder-7b-v9-auto-distilled-direct-lora") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 17c150abafc9f976b21e65bcc89b3ee86a02619a55f15edff96edcc632de8ee3
- Size of remote file:
- 323 MB
- SHA256:
- 7e4443128112f3068e66be30f16dc892aeccda623329b15f53c8234f7010235a
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