# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("MTomita/CSC_51073_EP-Computer-Vision-Final-Project", dtype="auto")Quick Links
TimeSformer fine-tuned model
Checkpoint: timesformer_max_full_even_6.pt
Training configuration
- Model: TimeSformer-Base (Kinetics-400 pretrained)
- Frame sampling: even
- Data balancing: max_full
- Unfrozen last layers: 6
- Task: workout action classification (plank, push-up, squat, russian-twist)
Notes
This repository provides a raw PyTorch checkpoint.
To use it, load the checkpoint into a TimesformerForVideoClassification
model with the same configuration used during training.
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="MTomita/CSC_51073_EP-Computer-Vision-Final-Project")