Instructions to use rendchevi/text-to-code-v0.1-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rendchevi/text-to-code-v0.1-lora with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rendchevi/text-to-code-v0.1-lora", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "base_model_name_or_path": "neuphonic/neutts-nano", | |
| "bos_token_id": 128000, | |
| "eos_token_id": 128261, | |
| "freeze_base_model": true, | |
| "hidden_size": 576, | |
| "inference_mode": false, | |
| "lora_alpha": 32, | |
| "lora_bias": "none", | |
| "lora_dropout": 0.05, | |
| "lora_r": 16, | |
| "lora_target_modules": [ | |
| "q_proj", | |
| "k_proj", | |
| "v_proj", | |
| "o_proj" | |
| ], | |
| "lora_task_type": "CAUSAL_LM", | |
| "model_type": "speaker_conditioned_lora_wrapper", | |
| "pad_token_id": 128001, | |
| "speaker_dropout": 0.25, | |
| "speaker_embedding_dim": 256, | |
| "speaker_hidden_dim": 512, | |
| "speaker_token": "<|SPEAKER_TOKEN_POS|>", | |
| "speaker_token_id": 194246, | |
| "transformers_version": "5.6.2", | |
| "use_cache": false, | |
| "vocab_size": 194256 | |
| } | |