Instructions to use AmiraMohammed/FModelT1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use AmiraMohammed/FModelT1 with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("ybelkada/falcon-7b-sharded-bf16") model = PeftModel.from_pretrained(base_model, "AmiraMohammed/FModelT1") - Notebooks
- Google Colab
- Kaggle
File size: 750 Bytes
3eff363 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | {
"alpha_pattern": {},
"auto_mapping": null,
"base_model_name_or_path": "ybelkada/falcon-7b-sharded-bf16",
"bias": "none",
"fan_in_fan_out": false,
"inference_mode": true,
"init_lora_weights": true,
"layer_replication": null,
"layers_pattern": null,
"layers_to_transform": null,
"loftq_config": {},
"lora_alpha": 16,
"lora_dropout": 0.18543587894379265,
"megatron_config": null,
"megatron_core": "megatron.core",
"modules_to_save": [
"classifier",
"score"
],
"peft_type": "LORA",
"r": 8,
"rank_pattern": {},
"revision": null,
"target_modules": [
"query_key_value",
"dense",
"dense_h_to_4h",
"dense_4h_to_h"
],
"task_type": "SEQ_CLS",
"use_dora": false,
"use_rslora": false
} |