Instructions to use emmaoba/davanai-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use emmaoba/davanai-2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-4-mini-instruct") model = PeftModel.from_pretrained(base_model, "emmaoba/davanai-2") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": "<|endoftext|>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|endoftext|>", | |
| "is_local": false, | |
| "local_files_only": false, | |
| "model_max_length": 131072, | |
| "pad_token": "<|endoftext|>", | |
| "tokenizer_class": "TokenizersBackend", | |
| "unk_token": "<|endoftext|>" | |
| } | |