m365-expert-v3

from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "AYI-NEDJIMI/m365-expert-v3"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto")

messages = [
    {"role": "system", "content": "Tu es un expert en administration Microsoft 365."},
    {"role": "user", "content": "Comment migrer de Get-AzureADUser vers Microsoft Graph ?"}
]

text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(text, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.3)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))