Instructions to use Metadatasystem/Chatbot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Metadatasystem/Chatbot with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image-2.1-Turbo", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Metadatasystem/Chatbot") prompt = "Keras" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from Metadatasystem/Chatbot: direct link, hf CLI and curl.
- Browser
- Download file 673 Bytes
-
https://huggingface.co/Metadatasystem/Chatbot/resolve/main/README.md
- Command line
-
hf download hf://Metadatasystem/Chatbot/README.md
-
curl -L -o README.md https://huggingface.co/Metadatasystem/Chatbot/resolve/main/README.md
673 Bytes
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/received_2527690337640925.jpeg
text: Keras
parameters:
negative_prompt: Negatif
base_model: Qwen/Qwen-Image-2.1-Turbo
instance_prompt: '#'
license: afl-3.0
Assistent AI Iblis

- Prompt
- Keras
- Negative Prompt
- Negatif
Model description
Trigger words
You should use # to trigger the image generation.
Download model
Download them in the Files & versions tab.
