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 v5_dagger_model/checkpoint-180/scheduler.pt from ihaveadog/qwen25-vl-7b-browser-agent-lora: direct link, hf CLI and curl.
- Browser
- Download file 1.06 kB
-
https://huggingface.co/ihaveadog/qwen25-vl-7b-browser-agent-lora/resolve/main/v5_dagger_model/checkpoint-180/scheduler.pt
- Command line
-
hf download hf://ihaveadog/qwen25-vl-7b-browser-agent-lora/v5_dagger_model/checkpoint-180/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/ihaveadog/qwen25-vl-7b-browser-agent-lora/resolve/main/v5_dagger_model/checkpoint-180/scheduler.pt
1.06 kB
- Xet hash:
- da568d8ee6d680949142662ac158e081f827b1cae681f0ae7c53bb264d87f797
- Size of remote file:
- 1.06 kB
- SHA256:
- db10a462ddd938463497e09c4cc90b5fc5aae3e3f95255defedc7750b4e90de7
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