Instructions to use Anish13/dev_results_model8_new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Anish13/dev_results_model8_new with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import TransformerNet model = TransformerNet.from_pretrained("Anish13/dev_results_model8_new", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download best/config.json from Anish13/dev_results_model8_new: direct link, hf CLI and curl.
- Browser
- Download file 343 Bytes
-
https://huggingface.co/Anish13/dev_results_model8_new/resolve/main/best/config.json
- Command line
-
hf download hf://Anish13/dev_results_model8_new/best/config.json
-
curl -L -o config.json https://huggingface.co/Anish13/dev_results_model8_new/resolve/main/best/config.json
343 Bytes
| { | |
| "architectures": [ | |
| "TransformerNet" | |
| ], | |
| "d_model": 512, | |
| "dim_feedforward": 1024, | |
| "dropout": 0.1, | |
| "input_dim": 30000, | |
| "max_seq_len": 512, | |
| "model_type": "transformer", | |
| "nhead": 8, | |
| "num_decoder_layers": 6, | |
| "num_encoder_layers": 6, | |
| "output_dim": 30000, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.40.2" | |
| } | |