Instructions to use OfflineBase/Muse-Glimmer-30B-Lab-Decide-Support-Inbox-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use OfflineBase/Muse-Glimmer-30B-Lab-Decide-Support-Inbox-LoRA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Muse-Glimmer-30B-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "OfflineBase/Muse-Glimmer-30B-Lab-Decide-Support-Inbox-LoRA") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer.json
Browse files- .gitattributes +1 -0
- tokenizer.json +3 -0
.gitattributes
CHANGED
|
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
+
tokenizer.json filter=lfs diff=lfs merge=lfs -text
|
tokenizer.json
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c9dbee66967b58f31a7c27f723c3760da3526ccd0427578e8905b0abb0031c4d
|
| 3 |
+
size 28129897
|