Instructions to use ebrahimzaher/qwen_adaptive_tutor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ebrahimzaher/qwen_adaptive_tutor with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("./qwen_base_model") model = PeftModel.from_pretrained(base_model, "ebrahimzaher/qwen_adaptive_tutor") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from ebrahimzaher/qwen_adaptive_tutor: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/ebrahimzaher/qwen_adaptive_tutor/resolve/main/tokenizer.json
- Command line
-
hf download hf://ebrahimzaher/qwen_adaptive_tutor/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ebrahimzaher/qwen_adaptive_tutor/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 81a4e2e141507c1f443f3c22e86c472e72b6615f7a2c93c1547fb244ab20b7c4
- Size of remote file:
- 11.4 MB
- SHA256:
- beed108eef3297c1ca17e51dafd053d3a4350ef41958cfdc947f6553d585723b
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