有示例，我在Google Colab T4笔记本上尝试了一下，但这是我得到的
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
torch.random.manual_seed(0)
model_path = "microsoft/Phi-4-mini-instruct"
model = AutoModelForCausalLM.from_pretrained(
model_path,
device_map="auto",
torch_dtype="auto",
trust_remote_code=True,
)
tokenizer = AutoTokenizer.from_pretrained(model_path)
messages = [
{"role": "system", "content": "You are a helpful AI assistant."},
{"role": "user", "content": "Can you provide ways to eat combinations of bananas and dragonfruits?"},
{"role": "assistant", "content": "Sure! Here are some ways to eat bananas and dragonfruits together: 1. Banana and dragonfruit smoothie: Blend bananas and dragonfruits together with some milk and honey. 2. Banana and dragonfruit salad: Mix sliced bananas and dragonfruits together with some lemon juice and honey."},
{"role": "user", "content": "What about solving an 2x + 3 = 7 equation?"},
]
pipe = pipeline(
"text-generation",
model=model,
tokenizer=tokenizer,
)
generation_args = {
"max_new_tokens": 500,
"return_full_text": False,
"temperature": 0.0,
"do_sample": False,
}
output = pipe(messages, **generation_args)
print(output[0]['generated_text'])
Device set to use cuda:0 /usr/local/lib/python3.11/dist-packages/transformers/generation/configuration_utils.py:628: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0.0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. warnings.warn(
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last) <ipython-input-3-c4a0ae4782d8> in <cell line: 0>()
19 }
20
---> 21 output = pipe(messages, **generation_args)
22 print(output[0]['generated_text'])
7 frames /usr/local/lib/python3.11/dist-packages/transformers/generation/utils.py in _sample(self, input_ids, logits_processor, stopping_criteria, generation_config, synced_gpus, streamer, **model_kwargs) 3307 3308 # update generated ids, model inputs, and length for next step
-> 3309 input_ids = torch.cat([input_ids, next_tokens[:, None]], dim=-1) 3310 if streamer is not None: 3311 streamer.put(next_tokens.cpu())
RuntimeError: Tensors must have same number of dimensions: got 2 and 3
我只是复制并粘贴了一个例子，我犯了什么错误？
huggingface上报告的标签问题：https：//huggingface.co/microsoft/phi-4-mini-instruct/discussions/14