Instructions to use adammandic87/75d4746c-5539-43c8-aeb9-ee3418b99286 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use adammandic87/75d4746c-5539-43c8-aeb9-ee3418b99286 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("dunzhang/stella_en_1.5B_v5") model = PeftModel.from_pretrained(base_model, "adammandic87/75d4746c-5539-43c8-aeb9-ee3418b99286") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from adammandic87/75d4746c-5539-43c8-aeb9-ee3418b99286: direct link, hf CLI and curl.
- Browser
- Download file 37.1 MB
-
https://huggingface.co/adammandic87/75d4746c-5539-43c8-aeb9-ee3418b99286/resolve/main/adapter_model.bin
- Command line
-
hf download hf://adammandic87/75d4746c-5539-43c8-aeb9-ee3418b99286/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/adammandic87/75d4746c-5539-43c8-aeb9-ee3418b99286/resolve/main/adapter_model.bin
37.1 MB
- Xet hash:
- 5273381b045acb6d959323dceac20085a2dfafb2940183faf1d91c277ccf584b
- Size of remote file:
- 37.1 MB
- SHA256:
- 0dc0ca653b5a849bc77e60435918876eb47350a1e65881de3b46f47f5120864f
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