Create app.py

app.py

@@ -0,0 +1,25 @@
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+model = AutoModelForCausalLM.from_pretrained("Vikhrmodels/Vikhr-7B-instruct_0.4",
+                                             device_map="auto",
+                                             attn_implementation="flash_attention_2",
+                                             torch_dtype=torch.bfloat16)
+
+tokenizer = AutoTokenizer.from_pretrained("Vikhrmodels/Vikhr-7B-instruct_0.4")
+from transformers import  AutoTokenizer, pipeline
+pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
+prompts = [
+    "В чем разница между фруктом и овощем?",
+    "Годы жизни колмагорова?"]
+
+def test_inference(prompt):
+    prompt = pipe.tokenizer.apply_chat_template([{"role": "user", "content": prompt}], tokenize=False, add_generation_prompt=True)
+    print(prompt)
+    outputs = pipe(prompt, max_new_tokens=512, do_sample=True, num_beams=1, temperature=0.25, top_k=50, top_p=0.98, eos_token_id=79097)
+    return outputs[0]['generated_text'][len(prompt):].strip()
+
+
+for prompt in prompts:
+    print(f"    prompt:\n{prompt}")
+    print(f"    response:\n{test_inference(prompt)}")
+    print("-"*50)