Hello :) Today is Day 115!
A quick summary of today:
- submitted 3rd homework of XCS224W:ML with Graphs
- explored different huggingface capabilities with DeepLearning.AI
As for the homework, we are not allowed to share anything from it. But I can happily share
I got full marks ^^
As for the huggingface tutorial
It showcased the different type of models that were available. Below is a summary.
Building a chat pipeline
Text translation
Text summarisation
Zero-shot audio classifier
Apparently, the model seens the audio differently - 1 second of high resolution audio appears to the model as if it is 12 seconds of audio.
Text to speech
Object detection
(code before the pic: od_pipe = pipeline(“object-detection”, “./models/facebook/detr-resnet-50”))
We can use gradio as a sample interface
I passed a picture of mine to check haha
We can also get natural language descriptions
Image captioning
Example image
Using the dog and woman pic again for multimodal QA
Zero-shot image classification
Giving labels: a photo of a cat, and a photo of a dog, we can get the models’ probs for each label.
Deploying a model
On hugging face to deploy a model, we need to:
- Create space
- Create requirements.txt and app.py files
After I created the two files, after a few minutes, the model was deployed and ready to be used.
In huggingface, the interface shows
I tested it with 2 images
Output: ‘a stone path’
Output: ‘a group of dogs sitting in a row’
It was a useful tutorial showcasing the code needed to run various open source models and perform various tasks.
That is all for today!
See you tomorrow :)