diff --git a/screenpipe-audio/src/stt.rs b/screenpipe-audio/src/stt.rs
index 35b7b9e8..49b9d8c9 100644
--- a/screenpipe-audio/src/stt.rs
+++ b/screenpipe-audio/src/stt.rs
@@ -5,17 +5,14 @@ use std::{
 
 use anyhow::{Error as E, Result};
 use candle::{Device, IndexOp, Tensor};
-use candle_nn::ops::softmax;
+use candle_nn::{ops::softmax, VarBuilder};
 use crossbeam::channel::{self, Receiver, Sender};
 use hf_hub::{api::sync::Api, Repo, RepoType};
 use log::{error, info};
 use rand::{distributions::Distribution, SeedableRng};
 use tokenizers::Tokenizer;
 
-use candle_transformers::{
-    models::whisper::{self as m, audio, Config},
-    quantized_var_builder::VarBuilder,
-};
+use candle_transformers::models::whisper::{self as m, audio, Config};
 use rubato::{
     Resampler, SincFixedIn, SincInterpolationParameters, SincInterpolationType, WindowFunction,
 };
@@ -37,24 +34,24 @@ impl WhisperModel {
         let (config_filename, tokenizer_filename, weights_filename) = {
             let api = Api::new()?;
             let repo = api.repo(Repo::with_revision(
-                "lmz/candle-whisper".to_string(),
+                "openai/whisper-tiny".to_string(),
                 RepoType::Model,
                 "main".to_string(),
             ));
-            let config = repo.get("config-tiny.json")?;
-            let tokenizer = repo.get("tokenizer-tiny.json")?;
-            let model = repo.get("model-tiny-q80.gguf")?;
+            let config = repo.get("config.json")?;
+            let tokenizer = repo.get("tokenizer.json")?;
+            let model = repo.get("model.safetensors")?;
             (config, tokenizer, model)
         };
 
         let config: Config = serde_json::from_str(&std::fs::read_to_string(config_filename)?)?;
         let tokenizer = Tokenizer::from_file(tokenizer_filename).map_err(E::msg)?;
 
-        let vb = VarBuilder::from_gguf(weights_filename, &device)?;
-        let model = Model::Quantized(m::quantized_model::Whisper::load(&vb, config)?);
-
+        let vb =
+            unsafe { VarBuilder::from_mmaped_safetensors(&[weights_filename], m::DTYPE, &device)? };
+        let model = Model::Normal(m::model::Whisper::load(&vb, config.clone())?);
         Ok(Self {
-            model: model,
+            model,
             tokenizer,
             device,
         })