Instructions to use BiniyamAjaw/llama-2-7b-finetuned-adapters with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use BiniyamAjaw/llama-2-7b-finetuned-adapters with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "BiniyamAjaw/llama-2-7b-finetuned-adapters") - Notebooks
- Google Colab
- Kaggle
| { | |
| "added_tokens_decoder": { | |
| "0": { | |
| "content": "[UNK]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "1": { | |
| "content": "[CLS]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "2": { | |
| "content": "[SEP]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "3": { | |
| "content": "[PAD]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "4": { | |
| "content": "[MASK]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| } | |
| }, | |
| "clean_up_tokenization_spaces": true, | |
| "max_length": null, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_to_multiple_of": null, | |
| "pad_token": "[PAD]", | |
| "pad_token_type_id": 0, | |
| "padding_side": "right", | |
| "tokenizer_class": "PreTrainedTokenizerFast" | |
| } | |