Instructions to use isashap/final3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use isashap/final3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("distilgpt2") model = PeftModel.from_pretrained(base_model, "isashap/final3") - Notebooks
- Google Colab
- Kaggle
| { | |
| "base_model_name_or_path": "distilgpt2", | |
| "inference_mode": true, | |
| "num_attention_heads": 12, | |
| "num_layers": 12, | |
| "num_transformer_submodules": 1, | |
| "num_virtual_tokens": 8, | |
| "peft_type": "PROMPT_TUNING", | |
| "prompt_tuning_init": "TEXT", | |
| "prompt_tuning_init_text": "Write a complete resume point for the given job.", | |
| "task_type": "CAUSAL_LM", | |
| "token_dim": 768, | |
| "tokenizer_name_or_path": "distilgpt2" | |
| } |