Instructions to use nblinh/88f6c0cf-8124-49b7-9e21-d30d565b42be with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nblinh/88f6c0cf-8124-49b7-9e21-d30d565b42be 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, "nblinh/88f6c0cf-8124-49b7-9e21-d30d565b42be") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from nblinh/88f6c0cf-8124-49b7-9e21-d30d565b42be: direct link, hf CLI and curl.
- Browser
- Download file 83.2 MB
-
https://huggingface.co/nblinh/88f6c0cf-8124-49b7-9e21-d30d565b42be/resolve/a0aac52976ea9bb7a4a2c6491f8e2c099dfcaa80/adapter_model.bin
- Command line
-
hf download hf://nblinh/88f6c0cf-8124-49b7-9e21-d30d565b42be@a0aac52976ea9bb7a4a2c6491f8e2c099dfcaa80/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/nblinh/88f6c0cf-8124-49b7-9e21-d30d565b42be/resolve/a0aac52976ea9bb7a4a2c6491f8e2c099dfcaa80/adapter_model.bin
83.2 MB
- Xet hash:
- 324d26a232b31e388ab333074fbcb086f13cbf624d9a90b358e33bcc19308df6
- Size of remote file:
- 83.2 MB
- SHA256:
- aa8f230b5b8a915665799ef28c391e424804076fb201d91d7697e273a578a1a9
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