Instructions to use daniel40/db57755b-c80b-4f73-82bc-02acf0262cbc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use daniel40/db57755b-c80b-4f73-82bc-02acf0262cbc with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-2-2b-it") model = PeftModel.from_pretrained(base_model, "daniel40/db57755b-c80b-4f73-82bc-02acf0262cbc") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from daniel40/db57755b-c80b-4f73-82bc-02acf0262cbc: direct link, hf CLI and curl.
- Browser
- Download file 41.7 MB
-
https://huggingface.co/daniel40/db57755b-c80b-4f73-82bc-02acf0262cbc/resolve/main/adapter_model.bin
- Command line
-
hf download hf://daniel40/db57755b-c80b-4f73-82bc-02acf0262cbc/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/daniel40/db57755b-c80b-4f73-82bc-02acf0262cbc/resolve/main/adapter_model.bin
41.7 MB
- Xet hash:
- d41e56342d847fe51af93a890f1200bf82fb1b24ddfa4dcb27ab06ae89ae5467
- Size of remote file:
- 41.7 MB
- SHA256:
- 5a31ec0dac66020eff2fd50c511a04e0df56962189f2d949290bfa7d5ef200f2
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