Instructions to use svjack/Qwen2-7B_Function_Call_tiny_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use svjack/Qwen2-7B_Function_Call_tiny_lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-7B-Instruct") model = PeftModel.from_pretrained(base_model, "svjack/Qwen2-7B_Function_Call_tiny_lora") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-200/tokenizer.json from svjack/Qwen2-7B_Function_Call_tiny_lora: direct link, hf CLI and curl.
- Browser
- Download file 7.03 MB
-
https://huggingface.co/svjack/Qwen2-7B_Function_Call_tiny_lora/resolve/main/checkpoint-200/tokenizer.json
- Command line
-
hf download hf://svjack/Qwen2-7B_Function_Call_tiny_lora/checkpoint-200/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/svjack/Qwen2-7B_Function_Call_tiny_lora/resolve/main/checkpoint-200/tokenizer.json
7.03 MB
File too large to display, you can check the raw version instead.