Homer-v1.0-Qwen2.5-72B is a fine-tuned version of Qwen2.5-72B using a large amount of instruction-based data.
How to use
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "newsbang/Homer-v1.0-Qwen2.5-72B"
model = AutoModelForCausalLM.from_pretrained(
model_name,
torch_dtype="auto",
device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained(model_name)
messages = [
{"role": "system", "content": "You are a very helpful assistant."},
{"role": "user", "content": "Hello"}
]
text = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True
)
model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
generated_ids = model.generate(
**model_inputs,
max_new_tokens=512
)
generated_ids = [
output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]
response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]