Instructions to use lorahub/flan_t5_large-dream_baseline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lorahub/flan_t5_large-dream_baseline with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-large") model = PeftModel.from_pretrained(base_model, "lorahub/flan_t5_large-dream_baseline") - Notebooks
- Google Colab
- Kaggle
File size: 411 Bytes
16dc2b3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | {
"base_model_name_or_path": "google/flan-t5-large",
"bias": "none",
"fan_in_fan_out": false,
"inference_mode": true,
"init_lora_weights": true,
"layers_pattern": null,
"layers_to_transform": null,
"lora_alpha": 32,
"lora_dropout": 0.1,
"modules_to_save": null,
"peft_type": "LORA",
"r": 16,
"revision": null,
"target_modules": [
"q",
"v"
],
"task_type": "SEQ_2_SEQ_LM"
} |