Instructions to use Lillyr/pretrain_v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Lillyr/pretrain_v0 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/lustre/fs11/portfolios/llmservice/users/zhidingy/wsh-ws/playground/region/checkpoint/VideoLLaMA3-2B-local") model = PeftModel.from_pretrained(base_model, "Lillyr/pretrain_v0") - Notebooks
- Google Colab
- Kaggle
Download non_lora_trainables.bin from Lillyr/pretrain_v0: direct link, hf CLI and curl.
- Browser
- Download file 955 MB
-
https://huggingface.co/Lillyr/pretrain_v0/resolve/main/non_lora_trainables.bin
- Command line
-
hf download hf://Lillyr/pretrain_v0/non_lora_trainables.bin
-
curl -L -o non_lora_trainables.bin https://huggingface.co/Lillyr/pretrain_v0/resolve/main/non_lora_trainables.bin
955 MB
- Xet hash:
- 0e8105898b3052858b6c27f128923451fe4d173c858151d567da3e20b29a6c19
- Size of remote file:
- 955 MB
- SHA256:
- 996d1ce97af9ee61444d4d66485fbb17c8e54a56efc793c5998d342039eb10af
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