Instructions to use MonsterMMORPG/Wan_GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MonsterMMORPG/Wan_GGUF with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MonsterMMORPG/Wan_GGUF", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
SECourses Video Captioner Pro — Complete Tutorial Images (v1.7.0)
SECourses Video Captioner Pro — tutorial image library
This first post hosts the 51 full-resolution annotated screenshots used by the complete SECourses Video Captioner Pro v1.7.0 tutorial. Each PNG is 3840 pixels wide.
The figures cover captioning, model and prompt controls, preprocessing, Whisper, multimodal chat, caption review, dataset export, settings and troubleshooting.
00 workspace
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01 first caption
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02 caption result
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03 caption complete
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04 native model
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05 block swap
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06 prompt library
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07 prompt variables
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08 generation
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09 gguf prefill
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10 gguf runtime
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11 sampling
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12 quality filters
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13 scene controls
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14 split quality
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15 postprocessing
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16 caption outputs
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17 transcript injection
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18 dataset audio
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19 dataset templates
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20 transcribe result
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21 whisper model
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22 whisper language
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23 whisper decode
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24 whisper output
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25 whisper vad
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26 chat conversation
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27 chat controls
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28 thinking
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30 editor review
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31 editor replace
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32 editor bulk
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33 editor export
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34 editor statistics
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35 editor filters
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36 editor regenerate
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40 trainer fitness
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41 dataset toml
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42 subsplit
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50 global settings
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51 recover settings
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52 system environment
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53 gguf runtime
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54 model actions
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55 native result
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56 batch zip
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57 shortcuts
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58 frame preview
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59 scene preview
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60 run history
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61 cancel
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