Instructions to use DB112/training1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DB112/training1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("ybelkada/falcon-7b-sharded-bf16") model = PeftModel.from_pretrained(base_model, "DB112/training1") - Notebooks
- Google Colab
- Kaggle
File size: 479 Bytes
37637f1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | {
"base_model_name_or_path": "ybelkada/falcon-7b-sharded-bf16",
"bias": "none",
"fan_in_fan_out": false,
"inference_mode": true,
"init_lora_weights": true,
"layers_pattern": null,
"layers_to_transform": null,
"lora_alpha": 16,
"lora_dropout": 0.1,
"modules_to_save": null,
"peft_type": "LORA",
"r": 64,
"revision": null,
"target_modules": [
"query_key_value",
"dense",
"dense_h_to_4h",
"dense_4h_to_h"
],
"task_type": "CAUSAL_LM"
} |