1、部署 text-embeddings-inference:cpu-1.5 上篇部署了 GPU 版本,这篇部署 CPU 架构的,为后续基准测试做准备。 根据官方代码仓库的容器镜像说明,支持 CPU 架构的标签为 cpu-1.5 如下图: 提供了不同架构下的镜像支持。这里选择 CPU 架构的进行部署和测试。 (1)拉取镜像 (base) ailearn@gpts:~$ docker pull...
ARG DOCKER_LABEL # sccache specific variables ARG ACTIONS_CACHE_URL ARG ACTIONS_RUNTIME_TOKEN ARG SCCACHE_GHA_ENABLED WORKDIR /usr/src RUN if [ ${CUDA_COMPUTE_CAP} -ge 75 -a ${CUDA_COMPUTE_CAP} -lt 80 ]; \ then \ nvprune --generate-code code=sm_${CUDA_COMPUTE_CAP} /usr/local/...
尽管该模型在基于英语的任务中存储和速度的使用效率高于OpenAI的`text-embedding-ada-002`,但在处理全球范围内的多语言任务(如跨不同社交媒体平台的情感分析)时,这一优势就被浪费了。由于Hugging Face通过这个高性能的gte-small模型以及与Docker兼容性和OpenAPI文档等服务保持了竞争优势,忽视多语言能力在其产品中造成了...
Dockerfile-cuda LICENSE Makefile README.md run.sh rust-toolchain.toml Latest commit OlivierDehaene v1.0.0 (huggingface#168) Feb 24, 2024 41b692d·Feb 24, 2024 History History Text Embeddings Inference A blazing fast inference solution for text embeddings models. ...
paddlenlp text模块 paddle embedding 2.2.2 召回模块 召回模块需要从千万量级数据中快速召回候选数据。首先需要抽取语料库中文本的 Embedding,然后借助向量搜索引擎实现高效 ANN,从而实现候选集召回。 我们针对不同的数据情况推出三种语义索引方案,如下图所示,您可以参照此方案,快速建立语义索引:...
A Dockerfile is provided to set up the environment. It installs Intel Extension for PyTorch 2.2 and sets up environment variables for optimal performance on Intel Xeon CPUs. After the Docker* image is compiled, start a container. The/root/llmdirectory will contain the example scripts. Alternativ...
model_id,model_version="huggingface-textgeneration-bloom-560m","*"# Retrieve the inference docker container urideploy_image_uri=image_uris.retrieve(region=None,framework=None,# automatically inferred from model_idimage_scope="inference",model_id=model_id,model_version=model_version,in...
which corresponds to about 860 mel spectrograms. Therefore the inference is expected to work well with generating audio samples of similar length. We set the mel spectrogram length limit to 2,000 (about 23 seconds), since in practice it still produces the correct voice. If needed, users can...
The encoder network consists of an embedding layer, followed by convolution layers with activations, and ends with a bidirectional LSTM. Because the encoder is only run one time during inference, it tends to take a small fraction of the runtime, less than five percent in most cases. ...
(BAAI general embedding)](https://github.com/shibing624/text2vec/blob/master/text2vec/bge_model.py):BGE模型按照[retromae](https://github.com/staoxiao/RetroMAE)方法进行预训练,[参考论文](https://aclanthology.org/2022.emnlp-main.35.pdf),再使用对比学习finetune微调训练模型,本项目基于PyTorch...