Comments (3)
shenlei1020
commented on July 4, 2024
本项目只有模型推理，没有服务部署相关代码。请问您的模型是怎么部署的？按照您部署去调用就行了
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shell-nlp
commented on July 4, 2024
本地部署了bce-reranker-base_v1模型后，go服务要怎么调用？没看到相关demo和说明
可以参考 我项目的部署方法，当然可以直接使用
https://github.com/shell-nlp/gpt_server/blob/main/tests/test_openai_rerank.py
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shell-nlp
commented on July 4, 2024
本项目只有模型推理，没有服务部署相关代码。请问您的模型是怎么部署的？按照您部署去调用就行了
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Related Issues (20)
- 使用 langchain 调用程序报错 HOT 2
- pydantic版本问题 HOT 1
- 下载 tokenizer 时不能指定 auth token HOT 2
- bce-reranker-base_v1原生支持的passage长度问题 HOT 1
- Are there any optimization methods to support the optimized run of this project? HOT 1
- RerankerModel的token数量 HOT 4
- 复现 LlamaIndex RAG评测结果时的一些问题 HOT 1
- Xinference对比手动部署 HOT 4
- 单独部署-用api的方式提供服务 HOT 1
- python3.11报错 HOT 1
- 请问有 C-MTEB （非英文）的测试结果么？ HOT 1
- 请问有没有提交到最新的mteb leaderboard的结果对比？
- 请问出现这种情况：Token indices sequence length is longer than the specified maximum sequence length for this model (781 > 512)，如何解决？ HOT 1
- query只能是一个句子吗？多轮交互下的召回或者排序，BCEEmbedding支持处理呢？ HOT 3
- Input validation error: `inputs` must have less than 512 tokens. Given: 1009 HOT 1
- accelerate加速，微调bce模型报错：Could not find the transformer layer class to wrap in the model. HOT 1
- FYI：最近测了 bce chunksize & bge 对比 HOT 2
- 请问如何在特定数据集上优化这个词向量模型？
- 为什么匹配效果越来越差 HOT 1
- embedding、rerank模型加速推理 HOT 8
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