我正在尝试在本地运行 DeepSeek VL2 模型（微型版本）并使用在Huggingface上找到的以下代码：
import torch
from transformers import AutoModelForCausalLM
from deepseek_vl.models import DeepseekVLV2Processor, DeepseekVLV2ForCausalLM
from deepseek_vl.utils.io import load_pil_images
# specify the path to the model
model_path = "deepseek-ai/deepseek-vl2-tiny" # replaced 'small' with 'tiny'
vl_chat_processor: DeepseekVLV2Processor = DeepseekVLV2Processor.from_pretrained(model_path)
tokenizer = vl_chat_processor.tokenizer
vl_gpt: DeepseekVLV2ForCausalLM = AutoModelForCausalLM.from_pretrained(model_path, trust_remote_code=True)
vl_gpt = vl_gpt.to(torch.bfloat16).cuda().eval()
## single image conversation example
conversation = [
{
"role": "<|User|>",
"content": "<image>\n<|ref|>The giraffe at the back.<|/ref|>.",
"images": ["./images/visual_grounding.jpeg"],
},
{"role": "<|Assistant|>", "content": ""},
]
# load images and prepare for inputs
pil_images = load_pil_images(conversation)
prepare_inputs = vl_chat_processor(
conversations=conversation,
images=pil_images,
force_batchify=True,
system_prompt=""
).to(vl_gpt.device)
# run image encoder to get the image embeddings
inputs_embeds = vl_gpt.prepare_inputs_embeds(**prepare_inputs)
# run the model to get the response
outputs = vl_gpt.language_model.generate(
inputs_embeds=inputs_embeds,
attention_mask=prepare_inputs.attention_mask,
pad_token_id=tokenizer.eos_token_id,
bos_token_id=tokenizer.bos_token_id,
eos_token_id=tokenizer.eos_token_id,
max_new_tokens=512,
do_sample=False,
use_cache=True
)
answer = tokenizer.decode(outputs[0].cpu().tolist(), skip_special_tokens=True)
print(f"{prepare_inputs['sft_format'][0]}", answer)
但是，我无法导入
from deepseek_vl.models import DeepseekVLV2Processor, DeepseekVLV2ForCausalLM
from deepseek_vl.utils.io import load_pil_images
我尝试通过 pip 安装 deepseek_vl，但那里列出的软件包名称相似，但看起来完全不同。于是我想，可能需要从 Github 下载 DeepSeek-VL 仓库。但该仓库不包含名为DeepseekVLV2Processor或DeepseekVLV2ForCausalLM的类models。不过，该load_pil_images函数可以在 或 下找到utils.io。
我知道 Huggingface 上的安装指南指出依赖项需要通过 来安装pip install -e .。但是我什么时候需要运行这个命令呢？下载仓库之后？显然，由于我是第一次在本地运行此类模型，所以我肯定是哪里做错了。我该如何运行上面的代码并正确导入依赖项呢？