Instructions to use keras/paraphrase_mpnet_base_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use keras/paraphrase_mpnet_base_v2 with KerasHub:
import keras_hub # Create a TextEmbedder model task = keras_hub.models.TextEmbedder.from_preset("hf://keras/paraphrase_mpnet_base_v2")import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://keras/paraphrase_mpnet_base_v2") - Keras
How to use keras/paraphrase_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/paraphrase_mpnet_base_v2") - Notebooks
- Google Colab
- Kaggle
File size: 1,617 Bytes
3c272d2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 | {
"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": 512,
"truncate": "round_robin"
},
"registered_name": "keras_hub>MPNetTextEmbedderPreprocessor"
} |