I ran the batch inference code with deepspeed generation, not the vllm one. The code hangs while I set zero stage = 3. I created a minimal code snippet for you to debug the error. importosimporttorchimporttorch.
Copy Step 2: Initialize the Inference Client importosfromhuggingface_hubimportInferenceClient# Initialize the client with your deployed endpoint and bearer tokenclient=InferenceClient(base_url="http://localhost:8080",api_key=os.getenv # Create a list of inputsbatch_inputs=[{"role":"user""conte...
While it should be possible to configure thebatch_sizeof the Hugging Face pipeline/model under the hood, this component only accepts aprompt(singlestr) as input, therefore this practically does not allow batching. Could you tell me more about your use case? Since the...
AI代码解释 sequences=["I've been waiting for a HuggingFace course my whole life.","This course is amazing!",]batch=tokenizer(sequences,padding=True,truncation=True,return_tensors="pt")batch['labels']=torch.tensor([1,1])# tokenizer出来的结果是一个dictionary,所以可以直接加入新的 key-value ...
从Huggingface Hub中加载数据集 数据集的预处理 Dataset.map方法有啥好处: Dynamic Padding 动态padding 「Huggingface NLP笔记系列-第6集」 最近跟着Huggingface上的NLP tutorial走了一遍,惊叹居然有如此好的讲解Transformers系列的NLP教程,于是决定记录一下学习的过程,分享我的笔记,可以算是官方教程的精简+注解版。但最...
url = "https://api-inference.huggingface.co/models/gpt2" headers = {"Authorization": "Bearer YOUR_API_KEY"} # 设置请求体,包括batch_size和输入数据 data = { "inputs": ["This is a sentence.", "This is another sentence."], "options": {"batch_size": 2} # 设置batch size ...
1classEmbedChunks:2def__init__(self):3self.embedding_model = HuggingFaceEmbeddings(4model_name="sentence-transformers/all-mpnet-base-v2"5)67def__call__(self, batch:Dict[str, np.ndarray]) ->Dict[str,list]:8results = FAISS.from_documents(batch["data"], self.embedding_model)9return{"embe...
inference_instance_type="ml.p3.2xlarge"# Retrieve the inference docker container uri. This is the base HuggingFace container image for the default model above.deploy_image_uri=image_uris.retrieve(region=None,framework=None,# automatically inferred from model_idima...
SageMaker 推理容器同时支持 HuggingFace 的 TGI 和 vLLM 两种动态 batch 框架,本文着重介绍 vLLM 框架在 SageMaker 上的使用。 SageMaker 使用 Large Model Inference(LMI)容器 inference 时,直接调用了 vLLM engine 的 step api,每次 iteration 迭代逐个输出 token 到输出队列,并调用 vLLM 状态 ...
与 PyTorch, TensorFlow, NVIDIA FasterTransformer, Microsoft DeepSpeed-Inference 等知名的深度学习库相比,ByteTransformer 在可变长输入下最高实现 131% 的加速。论文代码已开源。 机器之心 2023/08/04 1.4K0 torch.backends.cudnn.benchmark ?! 编程算法pytorch腾讯云测试服务批量计算卷积神经网络 大家在训练深度学习...