Instructions to use ihaveadog/qwen25-vl-7b-browser-agent-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ihaveadog/qwen25-vl-7b-browser-agent-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/qwen2.5-vl-7b-instruct") model = PeftModel.from_pretrained(base_model, "ihaveadog/qwen25-vl-7b-browser-agent-lora") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ihaveadog/qwen25-vl-7b-browser-agent-lora: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/ihaveadog/qwen25-vl-7b-browser-agent-lora/resolve/main/tokenizer.json
- Command line
-
hf download hf://ihaveadog/qwen25-vl-7b-browser-agent-lora/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ihaveadog/qwen25-vl-7b-browser-agent-lora/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- ab847c4f13ae9e85032d769de163de9d8459cc34b781c2d7c949969ee01cee6b
- Size of remote file:
- 11.4 MB
- SHA256:
- 741c85ffe434aad73e934a73ef380c85e94cd863b8f55e1a1ad66cacb5a93dfd
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