license: cc-by-nc-4.0
My model is a state-of-the-art language processing AI designed to understand and generate human-like text. It leverages deep learning algorithms to engage in a wide range of language tasks, providing users with information, recommendations, and even casual conversation. With a broad knowledge base and nuanced understanding of context, my capabilities enable me to assist with various inquiries and perform complex language-based tasks effectively.
How to use？
from transformers import AutoModelForCausalLM, AutoTokenizer from transformers.generation import GenerationConfig import torch
model = AutoModelForCausalLM.from_pretrained( 'TwT-6/open_llm_leaderboard_demo', attn_implementation="flash_attention_2", trust_remote_code=True, torch_dtype=torch.bfloat16, device_map="auto").eval() tokenizer = AutoTokenizer.from_pretrained('TwT-6/open_llm_leaderboard_demo', trust_remote_code=True) inputs = '你好' inputs = f'<|omni_start|>### User:\n{inputs}\n\n### Assistant:\n' inputs = tokenizer(inputs, return_tensors="pt").to('cuda')
output_ids = model.generate(**inputs)[0].cpu() output = tokenizer.decode(output_ids[inputs.input_ids.shape[-1]:])
print(output)