Instructions to use ma4389/LFM2-DPO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ma4389/LFM2-DPO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="ma4389/LFM2-DPO")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ma4389/LFM2-DPO") model = AutoModelForCausalLM.from_pretrained("ma4389/LFM2-DPO") - Notebooks
- Google Colab
- Kaggle
| { | |
| "backend": "tokenizers", | |
| "bos_token": "<|startoftext|>", | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": "<|im_end|>", | |
| "is_local": true, | |
| "legacy": false, | |
| "local_files_only": false, | |
| "model_input_names": [ | |
| "input_ids", | |
| "attention_mask" | |
| ], | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<|pad|>", | |
| "sp_model_kwargs": {}, | |
| "spaces_between_special_tokens": false, | |
| "tokenizer_class": "TokenizersBackend", | |
| "use_default_system_prompt": false, | |
| "use_fast": true | |
| } | |