Instructions to use FinchResearch/DeciCoder-ft-HTML with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use FinchResearch/DeciCoder-ft-HTML with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Deci/DeciCoder-1b") model = PeftModel.from_pretrained(base_model, "FinchResearch/DeciCoder-ft-HTML") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from FinchResearch/DeciCoder-ft-HTML: direct link, hf CLI and curl.
- Browser
- Download file 32.8 MB
-
https://huggingface.co/FinchResearch/DeciCoder-ft-HTML/resolve/main/adapter_model.bin
- Command line
-
hf download hf://FinchResearch/DeciCoder-ft-HTML/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/FinchResearch/DeciCoder-ft-HTML/resolve/main/adapter_model.bin
32.8 MB
- Xet hash:
- 4e9e10830fe6d32be6f7337ceac1203da4c0bfd9d173b5eb16847d25aba80b8e
- Size of remote file:
- 32.8 MB
- SHA256:
- a32bdaaf1f781db88c5b6352d07bc632a33472a27e385f312d335006a3128771
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