Update app.py

Language translation model without pipeline API.

app.py

@@ -1,4 +1,4 @@
-from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
+from transformers import AutoModel, AutoModelForSeq2SeqLM, AutoModelForQuestionAnswering, AutoTokenizer, pipeline
 import gradio as grad
 import ast
 
@@ -21,11 +21,27 @@ import ast
 
 # 3. Different task: language translation.
 # First model translates English to German.
-mdl_name = "Helsinki-NLP/opus-mt-en-de"
-opus_translator = pipeline("translation", model=mdl_name)
+# mdl_name = "Helsinki-NLP/opus-mt-en-de"
+# opus_translator = pipeline("translation", model=mdl_name)
+
+# def translate(text):
+#     response = opus_translator(text)
+#     return response
+
+# grad.Interface(translate, inputs=["text",], outputs="text").launch()
+
+# 4. Language translation without pipeline API.
+# Second model translates English to French.
+mdl_name = "Helsinki-NLP/opus-mt-en-fr"
+mdl = AutoModelForSeq2SeqLM.from_pretrained(mdl_name)
+my_tkn = AutoTokenizer.from_pretrained(mdl_name)
 
 def translate(text):
-    response = opus_translator(text)
+    inputs = my_tkn(text, return_tensors="pt")
+    trans_output = mdl.generate(**inputs)
+    response = my_tkn.decode(trans_output[0], skip_special_tokens=True)
     return response
 
-grad.Interface(translate, inputs=["text",], outputs="text").launch()
+txt=grad.Textbox(lines=1, label="English", placeholder="English Text here")
+out=grad.Textbox(lines=1, label="French")
+grad.Interface(translate, inputs=txt, outputs=out).launch()