Instructions to use cointegrated/SONAR_200_converted_text_decoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cointegrated/SONAR_200_converted_text_decoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="cointegrated/SONAR_200_converted_text_decoder", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("cointegrated/SONAR_200_converted_text_decoder", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "activation_dropout": 0.1, | |
| "activation_function": "relu", | |
| "architectures": [ | |
| "SonarDecoderModel" | |
| ], | |
| "attention_dropout": 0.1, | |
| "auto_map": { | |
| "AutoConfig": "sonar_decoder.SonarDecoderConfig", | |
| "AutoModel": "sonar_decoder.SonarDecoderModel", | |
| "AutoModelForSeq2SeqLM": "sonar_decoder.SonarDecoderModel" | |
| }, | |
| "bos_token_id": 0, | |
| "d_model": 1024, | |
| "decoder_attention_heads": 16, | |
| "decoder_ffn_dim": 8192, | |
| "decoder_layerdrop": 0, | |
| "decoder_layers": 24, | |
| "decoder_start_token_id": 2, | |
| "dropout": 0.1, | |
| "dtype": "float32", | |
| "encoder_attention_heads": 16, | |
| "encoder_ffn_dim": 8192, | |
| "encoder_layerdrop": 0, | |
| "encoder_layers": 24, | |
| "eos_token_id": 2, | |
| "init_std": 0.02, | |
| "is_encoder_decoder": true, | |
| "max_position_embeddings": 1024, | |
| "model_type": "SonarDecoderModel", | |
| "num_hidden_layers": 24, | |
| "pad_token_id": 1, | |
| "scale_embedding": true, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.0.0", | |
| "use_cache": true, | |
| "vocab_size": 256206 | |
| } | |