Instructions to use jianna4/sent.analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jianna4/sent.analysis with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Phr00t/Qwen-Image-Edit-Rapid-AIO", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("jianna4/sent.analysis") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Phr00t/Qwen-Image-Edit-Rapid-AIO", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("jianna4/sent.analysis")
prompt = "-"
image = pipe(prompt).images[0]sent.analy
- Prompt
- -
Model description
this is a sentimental analysis model formed tp predict posistive an negtive texts.It uses the imdb dataset for training
Trigger words
You should use imdb to trigger the image generation.
You should use senimentalanalysis to trigger the image generation.
Download model
Download them in the Files & versions tab.
- Downloads last month
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Model tree for jianna4/sent.analysis
Base model
Qwen/Qwen-Image-Edit-2511 Finetuned
Phr00t/Qwen-Image-Edit-Rapid-AIO