A web interface for chatting with Alpaca through llama.cpp. Fully dockerized, with an easy to use API. - serge-chat/serge
To set up vision-based reasoning tasks with Llama 3.2 models in Amazon Bedrock, use the following code snippet: importboto3importjsonimportbase64frombotocore.configimportConfig# Initialize the Bedrock clientconfig=Config(region_name=os.getenv("BEDROCK_REGION","us-west-2"),)bedroc...
Easy-to-use and powerful LLM and SLM library with awesome model zoo. paddlenlp.readthedocs.io Topics nlpsearch-enginecompressionsentiment-analysistransformersinformation-extractionquestion-answeringllamapretrained-modelsembeddingbertsemantic-analysisdistributed-trainingernieneural-searchuiedocument-intelligencepaddlenlp...
Meta Llama models deployed as a serverless API are offered by Meta through the Azure Marketplace and integrated with Azure AI Foundry for use. You can find the Azure Marketplace pricing when deploying the model.Each time a project subscribes to a given offer from the Azure Marketplace, a ...
于是为了促进开源大模型工具使用能力的建设,研究人员提出了一个通用的tool-use框架ToolLLM,包括构建数据集ToolBench,设计自动评估方案ToolEval,并基于此训练了一个语言模型ToolLLaMA,在工具使用的表现足以媲美ChatGPT。 图2: ToolBench构建过程,两个模型训练方式以及具体推理过程 2 背景 Tool learning旨在释放大规模语言...
Custom and local models often provide access via REST APIs, for example see Ollama OpenAI compatibility. Before you integrate your model it will need to be hosted and accessible to your .NET application via HTTPS. Prerequisites An Azure account with an active subscription. Create an account for...
Open-source models, e.g. adopting Llama as a model provider or for further fine-tuning We will work with excellent open-source models like Llama, by providing them as model options in our platform, or using them for further fine-tuning. ...
and integrations with popular tools such as LangChain, LlamaIndex, Weights & Biases, and many more. Deep Lake works with data of any size, it is serverless, and it enables you to store all of your data in your own cloud and in one place. Deep Lake is used by Intel, Bayer Radiology...
This is especially important for enterprise generative AI as it allows enterprises to train their own LLMs using sensitive data that they may not want to share with cloud or LLM providers. See the Meta LlaMa 3.1 models, their use cases, and benchmark to leading models: Meta LlaMa 3.1 In ...
With the Llama-2 7B chat model loaded into memory and the embeddings integrated into the Pinecone index, you can now combine these elements to enhance Llama 2’s responses for our question-answering use case. To achieve this, you ca...