A word-level LSTM encoder-decoder trained on a Hindi-English parallel corpus.
1import pickle, numpy as np, tensorflow as tf
2from huggingface_hub import hf_hub_download
3
4repo_id = "sajalkuikel/eng-to-hindi-seq2seq"
5encoder_model = tf.keras.models.load_model(hf_hub_download(repo_id, "encoder_model.keras"))
6decoder_model = tf.keras.models.load_model(hf_hub_download(repo_id, "decoder_model.keras"))
7eng_tokenizer = pickle.load(open(hf_hub_download(repo_id, "eng_tokenizer.pkl"), "rb"))
8hin_tokenizer = pickle.load(open(hf_hub_download(repo_id, "hin_tokenizer.pkl"), "rb"))
9config = pickle.load(open(hf_hub_download(repo_id, "model_config.pkl"), "rb"))
See the linked Space for a live demo with full inference code.