TALM: Tool Augmented Language Models Toolformer: Language Models Can Teach Themselves to Use Tools 填充式工具使用 + InContext制造自监督样本 Toolformer是工具调用领域的前辈,使用LM监督微调得到可以进行Inline工具调用的模型。解码时,模型会在恰当的位置生成API调用的请求,并中止解码,去调用API得到返回值,把返回...
Toolformer TALM: Tool Augmented Language Models Toolformer: Language Models Can Teach Themselves to Use Tools 填充式工具使用 + InContext制造自监督样本 Toolformer是工具调用领域的前辈,使用LM监督微调得到可以进行Inline工具调用的模型。解码时,模型会在恰当的位置生成API调用的请求,并中止解码,去调用API得到返回...
Opportunities for retrieval and tool augmented large language models in scientific facilitiesUpgrades to advanced scientific user facilities such as next-generation x-ray light sources, nanoscience centers, and neutron facilities are revolutionizing our understanding of materials across the spectrum of the ...
Toolformer TALM: Tool Augmented Language Models Toolformer: Language Models Can Teach Themselves to Use Tools 填充式工具使用 + InContext制造自监督样本 Toolformer是工具调用领域的前辈,使用LM监督微调得到可以进行Inline工具调用的模型。解码时,模型会在恰当的位置生成API调用的请求,并中止解码,去调用API得到返回...
TALM: Tool Augmented Language Models Toolformer: Language Models Can Teach Themselves to Use Tools 填充式工具使用 + InContext制造自监督样本 Toolformer是工具调用领域的前辈,使用LM监督微调得到可以进行Inline工具调用的模型。解码时,模型会在恰当的位置生成API调用的请求,并中止解码,去调用API得到返回值,把返回...
TALM: Tool Augmented Language Models Toolformer: Language Models Can Teach Themselves to Use Tools 填充式工具使用 + InContext制造自监督样本Toolformer是工具调用领域的前辈,使用LM监督微调得到可以进行Inline工具调用的模型。解码时,模型会在恰当的位置生成API调用的请求,并中止解码,去调用API得到返回值,把返回...
tie_weights() >>> model = load_checkpoint_and_dispatch(model, model_path, device_map="auto", no_split_module_classes=["MossBlock"], dtype=torch.float16) >>> meta_instruction = "You are an AI assistant whose name is MOSS.\n- MOSS is a conversational language model that is developed...
(qin et al., 2023). toolllm is an in-context learning approach to tool-augmented language models. it utilizes an instruction-tuned llama-7b model (touvron et al., 2023) to use tools. given the natural language instruction of a tool-dependent task, an api retriever first ...
ToolBeHonest aims at diagnosinghallucination issuesin large language models (LLMs) that are augmented with tools for real-world applications. We utilize a comprehensive diagnostic approach to assess LLMs' hallucinations through multi-level diagnostic processes and various toolset scenarios. ...
a tool-augmented LLM autonomous agent framework for practical and privacy-aware industrial RCA usage. Running on an internally deployed model rather than GPT families, RCAgent is capable of free-form data collection and comprehensive analysis with tools. Our framework combines a variety of enhancements...