Instructions to use cimol/85d5500f-577e-4c16-be0b-9b41451bd06e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cimol/85d5500f-577e-4c16-be0b-9b41451bd06e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3-8b") model = PeftModel.from_pretrained(base_model, "cimol/85d5500f-577e-4c16-be0b-9b41451bd06e") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/rng_state.pth from cimol/85d5500f-577e-4c16-be0b-9b41451bd06e: direct link, hf CLI and curl.
- Browser
- Download file 14.2 kB
-
https://huggingface.co/cimol/85d5500f-577e-4c16-be0b-9b41451bd06e/resolve/main/last-checkpoint/rng_state.pth
- Command line
-
hf download hf://cimol/85d5500f-577e-4c16-be0b-9b41451bd06e/last-checkpoint/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/cimol/85d5500f-577e-4c16-be0b-9b41451bd06e/resolve/main/last-checkpoint/rng_state.pth
14.2 kB
- Xet hash:
- 95c7192f9f7db4022886080967cf9e6a02ea6b53e40821d2917099c712cd5328
- Size of remote file:
- 14.2 kB
- SHA256:
- 40e2ad1636b456581f769716686c46886a3e77c7344b017b5ff6ec006db55a0f
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