|Published a new model type called Python Regex-Based Classifier|
- The new model type allows you to classify text using regex. If the regex matches, the text is classified as the provided concepts.
- If you're a Python coder who needs to do pattern-matching text classification (such as text moderation, LLM-based zero-shot, or auto-labeling), you can provide concepts and tag text inputs with the Regex-Based Classifier. Optionally, you can chain it together with many other models and operators in a workflow.
|Updated the default params values for the MMDetection__YoloF deep training template|
- The deep training template now has updated default parameter values.
|Replaced the “Train Model” button with a “Create New Model Version” button on the model viewer screen|
- The new button now more explicitly points to what you can achieve if you click it.
|Added a missing gear icon at the upper-right section of the model viewer page|
- Previously, there was a missing gear icon on the model viewer page. The icon is used to cache public preview predictions.
- The gear icon is now available, and you can use it to add public preview examples for non-logged-in users to see.
|Added preset inputs to appear on the left side of the Model-Viewer screen|
- If you open a model, inputs (thumbnails) now appear on the left side.
|Improved the design of the model version table and the training log monitor||If you create a model and hit the "train" button, you'll be redirected to the model version screen. |
- You can click the pencil button to edit a model version description and save it on the fly.
- You can get information about the status of the evaluation—the spinning wheel lets you check the status. You can also view the status message, view the training log monitor (for deep trained models only), retrain with a new version, and cancel the training.
- We've also added various action buttons for copying, deleting, and viewing a trained model version.
|Improved the design of the model versions dropdown list and "See versions table" button on the Model-Viewer screen|
- Model version selection is now more prominent than the previous semi-hidden view on the predict pane.
- If you select a model version, the predictions of that version will be rendered on the predict pane.
- You can also click the "See versions table" button to see the history of a model version.
|Fixed an issue where confusion matrix items appeared clogged in the evaluation results for datasets with many concepts, which complicated their viewing and interpretation|
- If you go to the evaluation results page to evaluate the performance of a model version, the items in the confusion matrix do not now appear clogged when you select many concepts.
|Fixed an issue where model training log details showed as loading even when training logs were not available|
- Previously, when the status for training a model showed as trained, the monitor kept showing that the training logs were being loaded. This happened because the embed-classifier model type does not have training logs.
- Currently, “View Logs” is only shown when logs are available.
|Fixed an issue where the prediction pane in the model viewer page of successfully user-trained models disappeared|
- The prediction pane of user-trained models now works as expected.
- The "Add Preview Images" and "Try Your Input" buttons are now working as expected.
|Fixed an issue where the initial prediction results of Clarifai's text models could not be rendered|
- Clarifai's text models now render first prediction results appropriately.
|Fixed an issue where the segmentation output mask size did not match the input image|
- If you open a visual segmentation model, the segmentation output mask size now matches the input image.
|Fixed an issue where the "Try your own Input" pop-up modal disappeared immediately||If you navigate to any visual-classifier or visual-detector model, either in your own app or Community, click the blue "+" icon on the left-hand side of the screen, a modal will appear asking you to upload an image to try the model. |
- Previously, the modal could disappear immediately. After fixing the issue, the modal now stays open and waits for the user to choose an image.