Video-Text-to-Text
PEFT
TensorBoard
Safetensors
Transformers
llama-factory
lora
video-language-model
pet-detection
Instructions to use Raullen/petvlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Raullen/petvlm with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-VL-2B-Instruct") model = PeftModel.from_pretrained(base_model, "Raullen/petvlm") - Transformers
How to use Raullen/petvlm with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Raullen/petvlm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Raullen/petvlm: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/Raullen/petvlm/resolve/main/tokenizer.json
- Command line
-
hf download hf://Raullen/petvlm/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Raullen/petvlm/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 9634a13dce23097940ed18824bf83f15fb90710cb158f7ae03a04ac6043c6ba6
- Size of remote file:
- 11.4 MB
- SHA256:
- 091aa7594dc2fcfbfa06b9e3c22a5f0562ac14f30375c13af7309407a0e67b8a
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