Visual Question Answering
Transformers
Safetensors
Chinese
English
QH_360VL
text-generation
custom_code
Instructions to use ecfirst/360VL_PHI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ecfirst/360VL_PHI with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "visual-question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("visual-question-answering", model="ecfirst/360VL_PHI", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("ecfirst/360VL_PHI", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model-00001-of-00004.safetensors from ecfirst/360VL_PHI: direct link, hf CLI and curl.
- Browser
- Download file 4.98 GB
-
https://huggingface.co/ecfirst/360VL_PHI/resolve/main/model-00001-of-00004.safetensors
- Command line
-
hf download hf://ecfirst/360VL_PHI/model-00001-of-00004.safetensors
-
curl -L -o model-00001-of-00004.safetensors https://huggingface.co/ecfirst/360VL_PHI/resolve/main/model-00001-of-00004.safetensors
4.98 GB
- Xet hash:
- a7873cd48057986e91e65291e5bad8806e82c61842888bde74e5227ccc6606b5
- Size of remote file:
- 4.98 GB
- SHA256:
- ecd95a8decd9193c4d5e62cd3e2310705ab0578ad3b70dca419ecdcc4db07070
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.