small fixes

HF Login Snippet Kaggle.py

@@ -5,8 +5,8 @@ from huggingface_hub import login, get_token, whoami
 
 #get token
 if os.environ.get('KAGGLE_KERNEL_RUN_TYPE', None) is not None: #check if user in kaggle
-    from kaggle_secrets import UserSecretsClient
-    from kaggle_web_client import BackendError
+    from kaggle_secrets import UserSecretsClient # type: ignore
+    from kaggle_web_client import BackendError # type: ignore
     try:
         login(UserSecretsClient().get_secret("HF_TOKEN")) #login if token secret found
     except BackendError: 

README.md

@@ -40,7 +40,7 @@ Feel free to send in PRs or use this code however you'd like.\
 
 - EXL2 Private Quant
   - Allows you to quantize to exl2 using colab. This version creates a exl2 quant to upload to private repo. Should work on any Linux jupyterlab server with CUDA, ROCM should be supported by exl2 but not tested.
- 
+
 - Upload folder to repo
   - Uploads user specified folder to specified repo, can create private repos too. Not the same as git commit and push, instead uploads any additional files.
   

manage branches.py

@@ -1,5 +1,6 @@
 #import required modules
 import os
+import sys
 from huggingface_hub import create_branch, delete_branch, login, get_token, whoami
 
 #define clear screen function
@@ -62,8 +63,8 @@ clear_screen()
 
 #get token
 if os.environ.get('KAGGLE_KERNEL_RUN_TYPE', None) is not None: #check if user in kaggle
-    from kaggle_secrets import UserSecretsClient
-    from kaggle_web_client import BackendError
+    from kaggle_secrets import UserSecretsClient # type: ignore
+    from kaggle_web_client import BackendError # type: ignore
     try:
         login(UserSecretsClient().get_secret("HF_TOKEN")) #login if token secret found
     except BackendError: 

requirements.txt

@@ -1,3 +0,0 @@
-huggingface-hub>=0.20.0
-requests
-tqdm

upload folder to repo.py

@@ -18,8 +18,8 @@ clear_screen()
 
 #get token
 if os.environ.get('KAGGLE_KERNEL_RUN_TYPE', None) is not None: #check if user in kaggle
-    from kaggle_secrets import UserSecretsClient
-    from kaggle_web_client import BackendError
+    from kaggle_secrets import UserSecretsClient # type: ignore
+    from kaggle_web_client import BackendError # type: ignore
     try:
         login(UserSecretsClient().get_secret("HF_TOKEN")) #login if token secret found
     except BackendError: