Summarization
Transformers
PyTorch
Safetensors
multilingual
miscovery
transformer
translation
question-answering
english
arabic
Instructions to use miscovery/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use miscovery/model with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="miscovery/model")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("miscovery/model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "CustomTransformerModel" | |
| ], | |
| "bos_token_id": 2, | |
| "d_ff": 2048, | |
| "d_model": 512, | |
| "dropout": 0.05, | |
| "eos_token_id": 3, | |
| "max_position_embeddings": 300, | |
| "model_type": "miscovery", | |
| "num_decoder_layers": 8, | |
| "num_encoder_layers": 8, | |
| "num_heads": 8, | |
| "pad_token_id": 0, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.35.2", | |
| "use_flash_attn": true, | |
| "vocab_size": 50000 | |
| } | |