Instructions to use dimasik87/ed20e542-9648-402a-845b-f096cbb99cfc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik87/ed20e542-9648-402a-845b-f096cbb99cfc with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("echarlaix/tiny-random-mistral") model = PeftModel.from_pretrained(base_model, "dimasik87/ed20e542-9648-402a-845b-f096cbb99cfc") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from dimasik87/ed20e542-9648-402a-845b-f096cbb99cfc: direct link, hf CLI and curl.
- Browser
- Download file 65.3 kB
-
https://huggingface.co/dimasik87/ed20e542-9648-402a-845b-f096cbb99cfc/resolve/main/adapter_model.bin
- Command line
-
hf download hf://dimasik87/ed20e542-9648-402a-845b-f096cbb99cfc/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/dimasik87/ed20e542-9648-402a-845b-f096cbb99cfc/resolve/main/adapter_model.bin
65.3 kB
- Xet hash:
- 2eb1b6ad9ccfcebf86768b48f28dde3f9434c37a06c672e265668c4cf18be426
- Size of remote file:
- 65.3 kB
- SHA256:
- 48d0c5682fdecb4babce2c4b9cf632be4de12af71152a42c17f7b8f75c4de3fe
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