Create app.py

app.py

@@ -0,0 +1,26 @@
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import gradio as gr
+
+# Load tokenizer and model manually
+tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1")
+model = AutoModelForCausalLM.from_pretrained(
+    "mistralai/Mistral-7B-Instruct-v0.1",
+    torch_dtype=torch.float16,
+    device_map="auto"  # uses GPU if available
+)
+
+def generate_text(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+    with torch.no_grad():
+        outputs = model.generate(
+            **inputs,
+            max_new_tokens=100,
+            do_sample=True,
+            temperature=0.7,
+            top_p=0.9,
+        )
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+# Create Gradio UI
+gr.Interface(fn=generate_text, inputs="text", outputs="text", title="Manual Mistral").launch()