Update README.md

README.md

@@ -18,7 +18,6 @@ frameworks:
 
 ---
 
-
 # Dolphin-Fangyan
 
 [Paper](https://arxiv.org/abs/2503.20212)
@@ -98,8 +97,8 @@ Currently, Dolphin-Fangyan provides multiple model sizes optimized for different
 |:------:|:----------:|:----------:|
 |  base.fangyan  |    74 M   | ❌ |
 |  base.fangyan.streaming  |    74 M   |❌  |
-| small.fangyan  |   0.4 B      | Encode-biased Hotwords |
-| small.fangyan.streaming  |   0.4 B      | Encode-biased Hotwords |
+| small.fangyan  |   0.4 B      | Encoder-biased Hotwords |
+| small.fangyan.streaming  |   0.4 B      | Encoder-biased Hotwords |
 | small.fangyan.prompt |   0.4 B      | Prompt-based Hotwords |
 
 
@@ -193,8 +192,7 @@ import dolphin
 from dolphin import transcribe
 
 model_name = 'small.fangyan'
-model = dolphin.load_model(model_name, f"/home/duhu/.cache/dolphin/{model_name}", "cpu")
-# model = dolphin.load_model(model_name, f"/data/models/dolphin/{model_name}", "cpu")
+model = dolphin.load_model(model_name, f"/data/models/dolphin/{model_name}", "cuda")
 
 result = transcribe(model, 'audio.wav')
 print(result.text)
@@ -210,7 +208,7 @@ print(result.text)
 ## prompt-based hotwords
 
 model_name = 'small.fangyan.prompt'
-model = dolphin.load_model(model_name, f"/home/duhu/.cache/dolphin/{model_name}", "cpu")
+model = dolphin.load_model(model_name, f"/data/models/dolphin/{model_name}", "cuda")
 
 result = transcribe(model, 'audio.wav', hotwords=['诺香丹青牌科研胶囊'], use_prompt_hotword=True, use_two_stage_filter=True, decoding_method='attention')