Instructions to use aleegis10/54ec9177-6b0c-4506-bd1b-e600cdfd9a1a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use aleegis10/54ec9177-6b0c-4506-bd1b-e600cdfd9a1a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("fxmarty/tiny-dummy-qwen2") model = PeftModel.from_pretrained(base_model, "aleegis10/54ec9177-6b0c-4506-bd1b-e600cdfd9a1a") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/optimizer.pt from aleegis10/54ec9177-6b0c-4506-bd1b-e600cdfd9a1a: direct link, hf CLI and curl.
- Browser
- Download file 197 kB
-
https://huggingface.co/aleegis10/54ec9177-6b0c-4506-bd1b-e600cdfd9a1a/resolve/main/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://aleegis10/54ec9177-6b0c-4506-bd1b-e600cdfd9a1a/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/aleegis10/54ec9177-6b0c-4506-bd1b-e600cdfd9a1a/resolve/main/last-checkpoint/optimizer.pt
197 kB
- Xet hash:
- 6bbeae6e6b9b76b7f6e61cd1004fb41b00208db6bde7efaffd9c7a1f7caf665e
- Size of remote file:
- 197 kB
- SHA256:
- 48661efda7650864d5ad4df7e832ed61b59f6c350690b8aa9c309c0fe9898417
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