Instructions to use cimol/a42dd542-bf68-4fe7-a1e2-05d672b8be5f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cimol/a42dd542-bf68-4fe7-a1e2-05d672b8be5f with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-Coder-7B-Instruct") model = PeftModel.from_pretrained(base_model, "cimol/a42dd542-bf68-4fe7-a1e2-05d672b8be5f") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/rng_state.pth from cimol/a42dd542-bf68-4fe7-a1e2-05d672b8be5f: direct link, hf CLI and curl.
- Browser
- Download file 14.2 kB
-
https://huggingface.co/cimol/a42dd542-bf68-4fe7-a1e2-05d672b8be5f/resolve/main/last-checkpoint/rng_state.pth
- Command line
-
hf download hf://cimol/a42dd542-bf68-4fe7-a1e2-05d672b8be5f/last-checkpoint/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/cimol/a42dd542-bf68-4fe7-a1e2-05d672b8be5f/resolve/main/last-checkpoint/rng_state.pth
14.2 kB
- Xet hash:
- e6e51cdf01d6227fe5e246a351ebc81f2c79d1876af1dcb3caa039db77df5ddb
- Size of remote file:
- 14.2 kB
- SHA256:
- 02c000c4dcf270ab0a027ac3e0f66a4be028756dd5a689d731b4179ea569cca2
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