Instructions to use FatCat87/taopanda-2_b3db347c-a6bb-4682-9904-41bfd73f101a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use FatCat87/taopanda-2_b3db347c-a6bb-4682-9904-41bfd73f101a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("tiiuae/falcon-rw-1b") model = PeftModel.from_pretrained(base_model, "FatCat87/taopanda-2_b3db347c-a6bb-4682-9904-41bfd73f101a") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_prefix_space": false, | |
| "added_tokens_decoder": { | |
| "50256": { | |
| "content": "<|endoftext|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| } | |
| }, | |
| "bos_token": "<|endoftext|>", | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": "<|endoftext|>", | |
| "model_max_length": 1024, | |
| "pad_token": "<|endoftext|>", | |
| "tokenizer_class": "GPT2Tokenizer", | |
| "unk_token": "<|endoftext|>" | |
| } | |