feat: 增加 Cerebras 模型调用

app.py

@@ -1,7 +1,26 @@
 import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from transformers import pipeline
+
+tokenizer = AutoTokenizer.from_pretrained("cerebras/Cerebras-GPT-13B")
+model = AutoModelForCausalLM.from_pretrained("cerebras/Cerebras-GPT-13B")
+
+text = "Generative AI is "
+
+pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+def greet(speech):
+    generated_text = pipe(speech, max_length=50, do_sample=False, no_repeat_ngram_size=2)[0]
+    return generated_text['generated_text']
+
+# def greet(speech):
+#     inputs = tokenizer(speech, return_tensors="pt")
+#     outputs = model.generate(**inputs, num_beams=5, 
+#                             max_new_tokens=50, early_stopping=True,
+#                             no_repeat_ngram_size=2)
+#     text_output = tokenizer.batch_decode(outputs, skip_special_tokens=True)
+#     return text_output[0]
 
-def greet(name):
-    return "Hello " + name + "!!"
 
 iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+iface.launch(share=True)