Any-to-Any
Transformers
Safetensors
English
Chinese
qwen2_5_vl
text-generation
text-generation-inference
Instructions to use PaDT-MLLM/PaDT_Pro_7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PaDT-MLLM/PaDT_Pro_7B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSeq2SeqLM processor = AutoProcessor.from_pretrained("PaDT-MLLM/PaDT_Pro_7B") model = AutoModelForSeq2SeqLM.from_pretrained("PaDT-MLLM/PaDT_Pro_7B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from PaDT-MLLM/PaDT_Pro_7B: direct link, hf CLI and curl.
- Browser
- Download file 11.5 MB
-
https://huggingface.co/PaDT-MLLM/PaDT_Pro_7B/resolve/main/tokenizer.json
- Command line
-
hf download hf://PaDT-MLLM/PaDT_Pro_7B/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/PaDT-MLLM/PaDT_Pro_7B/resolve/main/tokenizer.json
11.5 MB
- Xet hash:
- 9486d275d37a4ae4e7c4057890e1445637776b66795e3bc0cc58b7b795e6508d
- Size of remote file:
- 11.5 MB
- SHA256:
- c565d026e69888e2e7e78ea543fce4e212a03d55ac13ebd72b0f056fb1010852
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