Instructions to use keras/all_mpnet_base_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use keras/all_mpnet_base_v2 with KerasHub:
import keras_hub # Create a TextEmbedder model task = keras_hub.models.TextEmbedder.from_preset("hf://keras/all_mpnet_base_v2")import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://keras/all_mpnet_base_v2") - Keras
How to use keras/all_mpnet_base_v2 with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://keras/all_mpnet_base_v2") - Notebooks
- Google Colab
- Kaggle
Download task.json from keras/all_mpnet_base_v2: direct link, hf CLI and curl.
- Browser
- Download file 3.19 kB
-
https://huggingface.co/keras/all_mpnet_base_v2/resolve/main/task.json
- Command line
-
hf download hf://keras/all_mpnet_base_v2/task.json
-
curl -L -o task.json https://huggingface.co/keras/all_mpnet_base_v2/resolve/main/task.json
3.19 kB
| { | |
| "module": "keras_hub.src.models.mpnet.mpnet_text_embedder", | |
| "class_name": "MPNetTextEmbedder", | |
| "config": { | |
| "backbone": { | |
| "module": "keras_hub.src.models.mpnet.mpnet_backbone", | |
| "class_name": "MPNetBackbone", | |
| "config": { | |
| "name": "mp_net_backbone", | |
| "trainable": true, | |
| "dtype": { | |
| "module": "keras", | |
| "class_name": "DTypePolicy", | |
| "config": { | |
| "name": "float32" | |
| }, | |
| "registered_name": null | |
| }, | |
| "vocabulary_size": 30527, | |
| "num_layers": 12, | |
| "num_heads": 12, | |
| "hidden_dim": 768, | |
| "intermediate_dim": 3072, | |
| "dropout": 0.1, | |
| "max_sequence_length": 512, | |
| "layer_norm_epsilon": 1e-05 | |
| }, | |
| "registered_name": "keras_hub>MPNetBackbone" | |
| }, | |
| "preprocessor": { | |
| "module": "keras_hub.src.models.mpnet.mpnet_text_embedder_preprocessor", | |
| "class_name": "MPNetTextEmbedderPreprocessor", | |
| "config": { | |
| "name": "mp_net_text_embedder_preprocessor", | |
| "trainable": true, | |
| "dtype": { | |
| "module": "keras", | |
| "class_name": "DTypePolicy", | |
| "config": { | |
| "name": "float32" | |
| }, | |
| "registered_name": null | |
| }, | |
| "tokenizer": { | |
| "module": "keras_hub.src.models.mpnet.mpnet_tokenizer", | |
| "class_name": "MPNetTokenizer", | |
| "config": { | |
| "name": "mp_net_tokenizer", | |
| "trainable": true, | |
| "dtype": { | |
| "module": "keras", | |
| "class_name": "DTypePolicy", | |
| "config": { | |
| "name": "int32" | |
| }, | |
| "registered_name": null | |
| }, | |
| "config_file": "tokenizer.json", | |
| "vocabulary": null, | |
| "sequence_length": null, | |
| "lowercase": true, | |
| "strip_accents": true, | |
| "split": true, | |
| "suffix_indicator": "##", | |
| "oov_token": "[UNK]", | |
| "special_tokens": null, | |
| "special_tokens_in_strings": false | |
| }, | |
| "registered_name": "keras_hub>MPNetTokenizer" | |
| }, | |
| "config_file": "preprocessor.json", | |
| "sequence_length": 384, | |
| "truncate": "round_robin" | |
| }, | |
| "registered_name": "keras_hub>MPNetTextEmbedderPreprocessor" | |
| }, | |
| "name": "mp_net_text_embedder", | |
| "pooling_mode": "mean", | |
| "normalize": true | |
| }, | |
| "registered_name": "keras_hub>MPNetTextEmbedder" | |
| } |