Instructions to use PinkPixel/ASCII-Machine with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PinkPixel/ASCII-Machine with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" 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("image-to-text", model="PinkPixel/ASCII-Machine")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("PinkPixel/ASCII-Machine") model = AutoModelForImageTextToText.from_pretrained("PinkPixel/ASCII-Machine") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use PinkPixel/ASCII-Machine with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for PinkPixel/ASCII-Machine to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for PinkPixel/ASCII-Machine to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for PinkPixel/ASCII-Machine to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="PinkPixel/ASCII-Machine", max_seq_length=2048, )
- Xet hash:
- 458bcbf483ed805b4297af928f717e64bd00c633a07be5fae5717cacbd48e2ef
- Size of remote file:
- 20 MB
- SHA256:
- 87a7830d63fcf43bf241c3c5242e96e62dd3fdc29224ca26fed8ea333db72de4
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