from transformers import AutoTokenizer, AutoModelForCausalLM
import transformers
import torch

model_id = "aeonium/Aeonium-v1.1-Chat-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    device_map="cuda",
    torch_dtype=torch.bfloat16,
)

chat = [
    { "role": "user", "content": "Привет!" },
]

prompt = tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=True)
inputs = tokenizer.encode(prompt, add_special_tokens=False, return_tensors="pt").to(model.device)
outputs = model.generate(input_ids=inputs, max_new_tokens=48)
print(tokenizer.decode(outputs[0]))

Content Warning

Aeonium v1.1 is a large language model trained on a broad dataset from the internet. As such, it may generate text that contains biases, offensive language, or other disapproving content. The model outputs should not be considered factual or representative of any individual's beliefs or identity. Users should exercise caution and apply careful filtering when using Aeonium's generated text, especially for sensitive or high-stakes applications. The developers do not condone generating harmful, biased, or unethical content.

Copyright

The model is released under the Apache 2.0 license.