Update app.py

app.py

@@ -1,16 +1,12 @@
-from transformers import ViTImageProcessor, ViTForImageClassification
-from PIL import Image
-import requests
+from transformers import AutoModelForCausalLM, AutoTokenizer
 
-url = 'http://images.cocodataset.org/val2017/000000039769.jpg'
-image = Image.open(requests.get(url, stream=True).raw)
+model_id = "mistralai/Mixtral-8x7B-Instruct-v0.1"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
 
-processor = ViTImageProcessor.from_pretrained('google/vit-base-patch16-224')
-model = ViTForImageClassification.from_pretrained('google/vit-base-patch16-224')
+model = AutoModelForCausalLM.from_pretrained(model_id)
 
-inputs = processor(images=image, return_tensors="pt")
-outputs = model(**inputs)
-logits = outputs.logits
-# model predicts one of the 1000 ImageNet classes
-predicted_class_idx = logits.argmax(-1).item()
-print("Predicted class:", model.config.id2label[predicted_class_idx])
+text = "Hello my name is"
+inputs = tokenizer(text, return_tensors="pt")
+
+outputs = model.generate(**inputs, max_new_tokens=20)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))