Instructions to use korbih/curriculum_2_lora_final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use korbih/curriculum_2_lora_final with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("korbih/Qwen2-VL-ui-sensei-curriculum-1-merged") model = PeftModel.from_pretrained(base_model, "korbih/curriculum_2_lora_final") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-69/tokenizer.json from korbih/curriculum_2_lora_final: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/korbih/curriculum_2_lora_final/resolve/main/checkpoint-69/tokenizer.json
- Command line
-
hf download hf://korbih/curriculum_2_lora_final/checkpoint-69/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/korbih/curriculum_2_lora_final/resolve/main/checkpoint-69/tokenizer.json
11.4 MB
- Xet hash:
- 85f2343a26d43a7e8deeae343e18f63775386b7548cf5cfa60957f39e2351030
- Size of remote file:
- 11.4 MB
- SHA256:
- 88a3a6fcb80132f76da8aa40cdc3fccd7e5d8468ef15421f5b0c2715e85217d2
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