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Qwen Mlp

This model detects 4 emotion states (Boredom, Engagement, Confusion, Frustration) from educational videos.

Sourcehuggingface.co/mapotofu40/qwen-mlp/tree/4845d75a02e314016d070a626984e52c98b7bde4
KindOtherBase modelQwen/Qwen2.5-7B-InstructVersionMlp Boredom bestCgrade

Model source

Kind
Other
File size
22.5 MB
Base model
Qwen/Qwen2.5-7B-Instruct
Version
vMlp Boredom best
Updated
Oct 24, 2026
Source
Hugging Face

Source description

DAiSEE Emotion Detection Model

This model detects 4 emotion states (Boredom, Engagement, Confusion, Frustration) from educational videos.

Architecture

  • Stage 1: Qwen2.5-VL-7B-Instruct (embedding extraction)
  • Stage 2: MLP classifiers (4 separate models)

Usage

Via Inference Endpoint

import requests
import base64

# Encode video
with open("student_video.avi", "rb") as f:
    video_b64 = base64.b64encode(f.read()).decode()

# Send request
response = requests.post(
    "https://YOUR-ENDPOINT.aws.endpoints.huggingface.cloud",
    headers={"Authorization": f"Bearer {YOUR_HF_TOKEN}"},
    json={"inputs": video_b64}
)

predictions = response.json()
print(predictions)

Sources

1 source
Hugging FacePrimaryVersion 4845d75a02e314016d070a626984e52c98b7bde4
huggingface.co/mapotofu40/qwen-mlp/tree/4845d75a02e314016d070a626984e52c98b7bde4

Verified Oct 24

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Model artifacts

4 artifacts

classifiers/mlp_Boredom_best.pth

pth · 22.5 MB · SHA-256 f28bdf950119…49cd · Hugging Face

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classifiers/mlp_Confusion_best.pth

pth · 22.5 MB · SHA-256 84a944d8374b…ccb7 · Hugging Face

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classifiers/mlp_Engagement_best.pth

pth · 22.5 MB · SHA-256 30f6d4ba31c7…cd34 · Hugging Face

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classifiers/mlp_Frustration_best.pth

pth · 22.5 MB · SHA-256 c453f23c03bf…522f · Hugging Face

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Source excerpts

2 excerpts
ReadmeAug 6huggingface.co/mapotofu40/qwen-mlp

--- license: apache-2.0 tags: - video-classification - emotion-detection - education - qwen2.5-vl library_name: transformers base_model: - Qwen/Qwen2.5-7B-Instruct --- # DAiSEE Emotion Detection Model This model detects 4 emotion states (Boredom, Engagement, Confusion, Frustration) from educational videos. ## Architecture - **Stage 1**: Qwen2.5-VL-7B-Instruct (embedding extraction) - **Stage 2**: MLP classifiers (4 separate models) ## Usage ### Via Inference Endpoint ```python import requests import base64 # Encode video with open("student_video.avi", "rb") as f: video_b64 = base64.b64encode(f.read()).decode() # Send request response = requests.post( "https://YOUR-ENDPOINT.aws.endpoints.huggingface.cloud", headers={"Authorization": f"Bearer {YOUR_HF_TOKEN}"}, json={"inputs": video_b64} ) predictions = response.json() print(predictions)

NoteAug 6huggingface.co/mapotofu40/qwen-mlp

Source context: 0 downloads · 1 likes · Pipeline video-classification · Library transformers · Repo mapotofu40/qwen-mlp