Instructions to use nhungphammmmm/1d572d52-d72b-445d-abc0-9b10b623991d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhungphammmmm/1d572d52-d72b-445d-abc0-9b10b623991d with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-6.7b-instruct") model = PeftModel.from_pretrained(base_model, "nhungphammmmm/1d572d52-d72b-445d-abc0-9b10b623991d") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d7dea104cfd911994956ffef9c2112bd6ea21e8da3b205f23f812d181c433252
- Size of remote file:
- 6.78 kB
- SHA256:
- f61a10ec87513cad664022c3a4131ff9b7dbe34bdaa7009750911cb35a0e12a5
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