Instructions to use samanehs/gpt2_imdb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use samanehs/gpt2_imdb with KerasHub:
import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://samanehs/gpt2_imdb") - Keras
How to use samanehs/gpt2_imdb with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://samanehs/gpt2_imdb") - Notebooks
- Google Colab
- Kaggle
| { | |
| "module": "keras_nlp.src.models.gpt2.gpt2_causal_lm_preprocessor", | |
| "class_name": "GPT2CausalLMPreprocessor", | |
| "config": { | |
| "name": "gpt2_causal_lm_preprocessor", | |
| "trainable": true, | |
| "dtype": "float32", | |
| "tokenizer": { | |
| "module": "keras_nlp.src.models.gpt2.gpt2_tokenizer", | |
| "class_name": "GPT2Tokenizer", | |
| "config": { | |
| "name": "gpt2_tokenizer", | |
| "trainable": true, | |
| "dtype": "int32", | |
| "sequence_length": null, | |
| "add_prefix_space": false | |
| }, | |
| "registered_name": "keras_nlp>GPT2Tokenizer" | |
| }, | |
| "sequence_length": 1024, | |
| "add_start_token": true, | |
| "add_end_token": true | |
| }, | |
| "registered_name": "keras_nlp>GPT2CausalLMPreprocessor" | |
| } |