Create app.py

app.py

@@ -0,0 +1,39 @@
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+from langchain_community.llms import HuggingFaceHub
+from langchain_community.llms import HuggingFaceTextGenInference
+
+# Load your Telugu model
+""" device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+model_name = "Telugu-LLM-Labs/Telugu-Llama2-7B-v0-Instruct"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16).to(device) """
+
+
+ENDPOINT_URL = "https://api-inference.huggingface.co/models/Telugu-LLM-Labs/Telugu-Llama2-7B-v0-Instruct"
+HF_TOKEN = ""
+
+llm = HuggingFaceTextGenInference(
+    inference_server_url=ENDPOINT_URL,
+    max_new_tokens=512,
+    top_k=50,
+    temperature=0.1,
+    repetition_penalty=1.03,
+    server_kwargs={
+        "headers": {
+            "Authorization": f"Bearer {HF_TOKEN}",
+            "Content-Type": "application/json",
+        }
+    },
+)
+
+def summarize(text, llm):
+     instruction = "కింది వచనాన్ని సంగ్రహించండి: "
+     prompt = instruction + text 
+     response = llm(prompt)
+     return response
+
+input_text = "గూగుల్ వార్తలు అనేది గూగుల్ ద్వారా అభివృద్ధి చేయబడిన వార్తా అగ్రిగేటర్ సేవ..." 
+result = summarize(input_text, llm)
+print(result)