hf offline decorator for tests to workaround rate limits (#2452) [skip ci]

* hf offline decorator for tests to workaround rate limits

* fail quicker so we can see logs

* try new cache name

* limit files downloaded

* phi mini predownload

* offline decorator for phi tokenizer

* handle meta llama 8b offline too

* make sure to return fixtures if they are wrapped too

* more fixes

* more things offline

* more offline things

* fix the env var

* fix the model name

* handle gemma also

* force reload of modules to recheck offline status

* prefetch mistral too

* use reset_sessions so hub picks up offline mode

* more fixes

* rename so it doesn't seem like a context manager

* fix backoff

* switch out tinyshakespeare dataset since it runs a py script to fetch data and doesn't work offline

* include additional dataset

* more fixes

* more fixes

* replace tiny shakespeaere dataset

* skip some tests for now

* use more robust check using snapshot download to determine if a dataset name is on the hub

* typo for skip reason

* use local_files_only

* more fixtures

* remove local only

* use tiny shakespeare as pretrain dataset and streaming can't be offline even if precached

* make sure fixtures aren't offline

improve the offline reset
try bumping version of datasets
reorder reloading and setting
prime a new cache
run the tests now with fresh cache
try with a static cache

* now run all the ci again with hopefully a correct cache

* skip wonky tests for now

* skip wonky tests for now

* handle offline mode for model card creation

tests/test_packed_pretraining.py

@@ -8,6 +8,7 @@ import torch
 from datasets import load_dataset
 from torch.utils.data import DataLoader
 from transformers import AutoTokenizer
+from utils import disable_hf_offline, enable_hf_offline
 
 from axolotl.utils.data import get_dataset_wrapper, wrap_pretraining_dataset
 from axolotl.utils.dict import DictDefault
@@ -18,17 +19,18 @@ class TestPretrainingPacking(unittest.TestCase):
     Test class for packing streaming dataset sequences
     """
 
+    @enable_hf_offline
     def setUp(self) -> None:
         # pylint: disable=duplicate-code
         self.tokenizer = AutoTokenizer.from_pretrained("huggyllama/llama-7b")
         self.tokenizer.pad_token = "</s>"
 
-    @pytest.mark.flaky(retries=3, delay=5)
+    @pytest.mark.flaky(retries=1, delay=5)
+    @disable_hf_offline
     def test_packing_stream_dataset(self):
         # pylint: disable=duplicate-code
         dataset = load_dataset(
-            "allenai/c4",
-            "en",
+            "winglian/tiny-shakespeare",
             streaming=True,
         )["train"]
 
@@ -36,8 +38,7 @@ class TestPretrainingPacking(unittest.TestCase):
             {
                 "pretraining_dataset": [
                     {
-                        "path": "allenai/c4",
-                        "name": "en",
+                        "path": "winglian/tiny-shakespeare",
                         "type": "pretrain",
                     }
                 ],