README.md

metadata

title: README
emoji: ❤️
colorFrom: red
colorTo: red
sdk: streamlit
app_file: app.py
pinned: false

Hugging Face makes it easy to collaboratively build and showcase your Sentence Transformers models!
You can collaborate with your organization, upload and showcase your own models in your profile! ❤️

Documentation

Push your Sentence Transformers models to the Hub ❤️

Find all Sentence Transformers models on the 🤗 Hub

To upload your Keras models to the Hub, you can use the push_to_hub_keras function.

!pip install huggingface-hub
!huggingface-cli login
from huggingface_hub.keras_mixin import push_to_hub_keras
push_to_hub_keras(model = model, repo_url = "https://huggingface.co/your-username/your-awesome-model")
    

To load Keras models from the 🤗Hub, use from_pretrained_keras function.

!pip install huggingface-hub
!huggingface-cli login
from huggingface_hub.keras_mixin import from_pretrained_keras
from_pretrained_keras("your-username/your-awesome-model)
    

If you'd like to upload 🤗Transformers based Keras checkpoints and let us host your metrics interactively in the repo in with TensorBoard, use PushToHubCallback like follows:

!pip install huggingface-hub
!huggingface-cli login
from transformers.keras_callbacks import PushToHubCallback
from tensorflow.keras.callbacks import TensorBoard
tensorboard_callback = TensorBoard(log_dir = "./logs/tensorboard)
push_to_hub_callback = PushToHubCallback(output_dir="./logs", 
                                        tokenizer=tokenizer,
                                        hub_model_id=model_id)

callbacks = [tensorboard_callback, push_to_hub_callback]
model.fit(..., callbacks=callbacks, ...)