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from transformers import AutoTokenizer, AutoModelForCausalLM
import gradio as gr
import torch
model_id = "ilsp/Meltemi-7B-Instruct-v1"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
device_map="auto",
load_in_4bit=True,
torch_dtype=torch.float16
)
def chat(user_input):
messages = [
{"role": "system", "content": "Είσαι το Μελτέμι, ένα γλωσσικό μοντέλο για την ελληνική γλώσσα."},
{"role": "user", "content": user_input}
]
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=256)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
return response
gr.Interface(fn=chat, inputs="text", outputs="text", title="Meltemi Chatbot 🇬🇷").launch()
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