Create README.md

README.md

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+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
+
+with ('generation_config.json').open('w') as fp:
+    json.dump({
+        "pad_token_id": 0,
+        "bos_token_id": 1,
+        "eos_token_id": 2,
+        "temperature": 0.3,
+        "top_p": 0.9,
+        "top_k": 50,
+        "do_sample": True,
+        "max_new_tokens": 1536,
+        "repetition_penalty": 1.1,
+        "no_repeat_ngram_size": 15,
+    }, fp, indent=4)
+
+MODEL_NAME = "Vikhrmodels/Vikhr_instruct"
+TEMPLATE = "<s>{role}\n{content}</s>\n"
+SYSTEM_PROMPT = "Ты – полезный помощник по имени Вихрь. Ты разговариваешь с людьми и помогаешь им."
+
+model = AutoModelForCausalLM.from_pretrained(MODEL_NAME)
+model.to('cuda')
+model.eval()
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, use_fast=False)
+generation_config = GenerationConfig.from_pretrained("generation_config.json")
+
+class Conversation:
+    def __init__(
+        self,
+        message_template=DEFAULT_MESSAGE_TEMPLATE,
+        system_prompt=DEFAULT_SYSTEM_PROMPT,
+    ):
+        self.message_template = message_template
+        self.messages = [{
+            "role": "system",
+            "content": system_prompt
+        }]
+
+    def add_user_message(self, message):
+        self.messages.append({
+            "role": "user",
+            "content": message
+        })
+
+    def get_prompt(self, tokenizer):
+        final_text = ""
+        for message in self.messages:
+            message_text = self.message_template.format(**message)
+            final_text += message_text
+        final_text += 'bot'
+        return final_text.strip()
+
+
+def generate(model, tokenizer, prompt, generation_config):
+    data = tokenizer(prompt, return_tensors="pt")
+    data = {k: v.to(model.device) for k, v in data.items()}
+    output_ids = model.generate(
+        **data,
+        generation_config=generation_config
+    )[0]
+    output_ids = output_ids[len(data["input_ids"][0]):]
+    output = tokenizer.decode(output_ids, skip_special_tokens=True)
+    return output.strip()
+
+inputs = ["Как тебя зовут?", "Кто такой Колмогоров?"]
+
+for inp in inputs:
+    conversation = Conversation()
+    conversation.add_user_message(inp)
+    prompt = conversation.get_prompt(tokenizer)
+
+    output = generate(model, tokenizer, prompt, generation_config)
+    print(inp)
+    print(output)
+```