Update app.py

app.py

@@ -1,24 +1,18 @@
-from mistral_inference.transformer import Transformer
-from mistral_inference.generate import generate
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
 
-from mistral_common.tokens.tokenizers.mistral import MistralTokenizer
-from mistral_common.protocol.instruct.messages import UserMessage, TextChunk, ImageURLChunk
-from mistral_common.protocol.instruct.request import ChatCompletionRequest
+# Hugging Face Model লোড করা
+model_id = "deepseek-ai/DeepSeek-R1"
 
-tokenizer = MistralTokenizer.from_file(f"{mistral_models_path}/tekken.json")
-model = Transformer.from_folder(mistral_models_path)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    trust_remote_code=True,
+    torch_dtype="auto",  # Automatic dtype (no FP8)
+    low_cpu_mem_usage=True  # কম মেমোরি ব্যবহার করবে
+)
 
-url = "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png"
-prompt = "Describe the image."
+tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
 
-completion_request = ChatCompletionRequest(messages=[UserMessage(content=[ImageURLChunk(image_url=url), TextChunk(text=prompt)])])
-
-encoded = tokenizer.encode_chat_completion(completion_request)
-
-images = encoded.images
-tokens = encoded.tokens
-
-out_tokens, _ = generate([tokens], model, images=[images], max_tokens=256, temperature=0.35, eos_id=tokenizer.instruct_tokenizer.tokenizer.eos_id)
-result = tokenizer.decode(out_tokens[0])
-
-print(result)
+# টেস্ট রান
+output = pipe("Hello, who are you?", max_length=100)
+print(output)