Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Fix code typo in int8-asr.mdx #698

Merged
merged 1 commit into from
Jul 14, 2023
+2 −2
Merged

Fix code typo in int8-asr.mdx #698

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 2 additions & 2 deletions docs/source/task_guides/int8-asr.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -205,7 +205,7 @@ Let's also apply LoRA to the training to make it even more efficient. Load a [`~
```py
from peft import LoraConfig, PeftModel, LoraModel, LoraConfig, get_peft_model

config = LoraConfig(r=32, lora_alpha=64, target_modules=["q_proj", "v_proj"], lora_dropout=0.05, bias="None")
config = LoraConfig(r=32, lora_alpha=64, target_modules=["q_proj", "v_proj"], lora_dropout=0.05, bias="none")
```

After you set up the [`~peft.LoraConfig`], wrap it and the base model with the [`get_peft_model`] function to create a [`PeftModel`]. Print out the number of trainable parameters to see how much more efficient LoRA is compared to fully training the model!
Expand Down Expand Up @@ -375,4 +375,4 @@ with torch.cuda.amp.autocast():
text = pipe(audio, generate_kwargs={"forced_decoder_ids": forced_decoder_ids}, max_new_tokens=255)["text"]
text
"मी तुमच्यासाठी काही करू शकतो का?"
```
```
Loading