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Archon provides a modular framework for combining different inference-time techniques and LMs with just a JSON config file. - Archon/archon/mt_bench/README.md at main · ScalingIntelligence/Archon
# env mt_benchgitclonehttps://github.com/lm-sys/FastChat.gitcdFastChat pip install -e".[model_worker,llm_judge]"python gen_judgment.py --model-list gpt-3.5-turbo gpt-4 --parallel 2 python show_result.py --model-list gpt-3.5-turbo gpt-4 mixtral...
Github:github.com/lm-sys/FastC 摘要Abstract Evaluating large language model (LLM) based chat assistants is challenging due to their broad capabilities and the inadequacy of existing benchmarks in measuring human preferences. To address this, we explore using strong LLMs as judges to evaluate the...
博客:https://wizardlm.github.io/WizardLM2/ 模型:https://huggingface.co/microsoft/WizardLM-2-8x22B 论文:即将发布 Deeplearning AI“量化基础”:学习如何量化几乎任何开源模型 链接:https://news.miracleplus.com/share_link/23439 ...
以下是我们得到的: **MiniCPM-V-2.6支持** ***合并**:[https://github.com/ggerganov/llama.cpp/pull/8967](https://github.com/ggerganov/llama.cpp/pull/8967) ***HF代表**:[https://huggingface.co/openbmb/MiniCPM-V-26.https://huggingface.co/openbmb/MiniCPM-V-2_6) ***GGUF**:[...
如何使用FastChat? | github: https://github.com/lm-sys/FastChatFastChat's core features include:The training and evaluation code for state-of-the-art models (e.g., Vicuna, MT-Bench).A distributed multi-model serving system with web UI and OpenAI-compatible RESTful APIs. ...
项目地址:https://github.com/lm-sys/FastChat/tree/main#vicuna-weights 在全新的评价系统下,GPT-4依然稳居第一,而GPT-3.5则成功夺回了第二的宝座。 Anthropic的两款Claude模型紧随其后,排在了第三和第四的位置上。 UC伯克利最新发布的330亿参数Vicuna进军第五,小幅领先微软华人团队开源的300亿参数WizardLM模型...
wget https://github.com/bazelbuild/bazel/releases/download/3.2.0/bazel-3.2.0-installer-linux-x86_64.sh --output-document bazel-installer.sh; travis_wait sudo bash bazel-installer.sh; fi - if [ "${TRAVIS_OS_NAME}" == "osx" ]; then curl -L -o bazel-installer.sh https://git...
在最新的9.1 SDK 上、不提供对 yolov6的端到端优化层支持。 但您可以在此处查看支持模型:https://github.com/TexasInstruments/edgeai-modelzoo?tab=readme-ov-file 您仍然可以使用 OSRT 进行模型编译、在该模型编译中、不受支持的图层将被委派给 ARM 进行推理。