relora: magnitude pruning of the optimizer (#1245)

* magnitude pruning of the optimizer

* add alpaca chat template and fix relora patch

* fix handling of lora adapter for relora

* fix merge and save call

* fixes for 8-bit lora merge

* save intermediate checkpoint adapters

* auto merge

* fix eval check

* handle relora annealing

* fix anneal step logic

* chore: lint

* misx fix

* fix types

* Update tests/e2e/test_relora_llama.py

* check for safetensors saved from relora

tests/e2e/patched/test_mistral_samplepack.py

@@ -7,8 +7,6 @@ import os
 import unittest
 from pathlib import Path
 
-from transformers.utils import is_torch_bf16_gpu_available
-
 from axolotl.cli import load_datasets
 from axolotl.common.cli import TrainerCliArgs
 from axolotl.train import train
@@ -63,6 +61,7 @@ class TestMistral(unittest.TestCase):
                 "max_steps": 20,
                 "save_steps": 10,
                 "eval_steps": 10,
+                "bf16": "auto",
             }
         )
         normalize_config(cfg)
@@ -103,12 +102,9 @@ class TestMistral(unittest.TestCase):
                 "max_steps": 20,
                 "save_steps": 10,
                 "eval_steps": 10,
+                "bf16": "auto",
             }
         )
-        if is_torch_bf16_gpu_available():
-            cfg.bf16 = True
-        else:
-            cfg.fp16 = True
         normalize_config(cfg)
         cli_args = TrainerCliArgs()
         dataset_meta = load_datasets(cfg=cfg, cli_args=cli_args)