Crowd EVAL
Bring human insight into your model checkpoints—before it's too late.
- Models miss obvious issues because automation lacks intuition.
- Standard Human eval happens too late or is too expensive.
- We provide you early warning signals from humans while training, for a fraction of the price.
What do we solve?
Capture real human sentiment
Model developers currently rely on specialised pre-trained evaluation models. However, these automated tools only emulate direct human feedback
By the time you will get some real people using your product, it's already too late
When can you leverage our tool?
Checkpoint is reached
Whenever you defined a checkpoint, the models stops to generate the images that will be used as a benchmark against 4o
Images get evaluated
Rapidata will take care of automating the pipelines needed to gather human feedback and provide you with insights
Gain insights
When the results are ready, they will be directly visualized in your Weights & Biases dashboard
Prices
$24 / For each evaluation
- You decide when to run evaluations during your training
- Price is based on evaluating 200 images, across 3 metrics: alignment, coherence and style, for a total of 6k answers
How simple is it?
All you need is a few lines of code
import wandb
from checkpoint_evaluation.image_checkpoint_evaluator import ImageEvaluator
# Initialize wandb
run = wandb.init(project="my-project")
# Create evaluator
evaluator = ImageEvaluator(wandb_run=run, model_name="my-model")
# In your training loop
for step in range(100):
# ... your training code ...
# Generate or load validation images (every N steps)
if step % 10 == 0:
# Fire-and-forget evaluation - returns immediately!
evaluator.evaluate(generate_images())
# ... continue training ...
# Wait for all evaluations to complete before finishing
evaluator.wait_for_all_evaluations()
run.finish()
pip install crowd-evalFeatures
Real human feedback at scale
- Collect large-scale human feedback without interrupting your training process
- Prevent overfitting and model collapse by incorporating diverse perspectives early and often
- Reduce engineering overhead by automating progress tracking
Capture human sentiments
- Access genuine human preferences that go beyond what any reward model can capture
- Evaluate your model with live human comparisons, similar to Hugging Face’s Image Arena—but integrated directly into your training loop
- Instantly visualise results inside your existing tools and dashboards
It just works
- No need to rethink your pipelines, everything is plug and play
- With just a few lines of code, you can access our global network of millions of annotators.