Google 《Prompt Engineering v7》Experiment with input formats and writing styles 59 For few-shot prompting with classification tasks, mix up the classes 59 Adapt to model updates 60 Experiment with output formats 60 JSON Repair 61 who is trying to trick the recipient into clicking on a malicious link or downloading a malicious file. **Conclusion: IMPORTANT** Based on the potential impact of the bug and the credibility of the sender Imagine a folder on your machine with hundreds of files that needs to be renamed. Renaming each file would take you a lot of time. You know a little Bash, and could write a script to automate this,0 码力 | 68 页 | 6.50 MB | 6 月前3
DeepSeek-V2: A Strong, Economical, and Efficient
Mixture-of-Experts Language ModelAbout Pre-Training Data Debiasing 32 F Additional Evaluations on Math and Code 33 G Evaluation Formats 34 3 1. Introduction In the past few years, Large Language Models (LLMs) (Anthropic, 2023; Google tokenizers. For an intuitive overview of these benchmarks, we additionally provide our evaluation formats for each benchmark in Appendix G. 3.2.2. Evaluation Results In Table 2, we compare DeepSeek-V2 from the period between September 1st, 2023 and April 1st, 2024. G. Evaluation Formats We present our evaluation formats for each benchmark in Table 12-37, respectively. PROMPT 以下是一道中国高考生物选择题,请选择正确的答案。0 码力 | 52 页 | 1.23 MB | 1 年前3
Trends Artificial Intelligence
pictures, sound, and video into a shared representation and generate outputs in any of those formats. A single query can reference a paragraph and a diagram, and the model can respond with a spoken annotated image – without switching systems. Each new modality forces models to align meaning across formats rather than optimize for one. The path to this capability unfolded stepwise: OpenAI’s CLIP paired Chameleon had become fully multimodal. Each new modality forced the models to align meaning across formats rather than optimize for one. The payoff is practical. A field engineer can aim a phone camera0 码力 | 340 页 | 12.14 MB | 5 月前3
亿联TVM部署kinds of hardware platform: Intel/arm CPU, Nividia/arm GPU, VTA…5 �������������� 1. Get a .log file from the autotvm on Ubuntu 2. Use the .log from step1 on Windows to generate the .dll for deployment0 码力 | 6 页 | 1.96 MB | 6 月前3
Deploy VTA on Intel FPGAvta_config.json Step 9: Go to vta/hardware/intel and run make command Step 10: Get the generated .sof file programmed into hardware Step 11: Evaluate the unit test script test_vta_insn.py with python3. Hooray0 码力 | 12 页 | 1.35 MB | 6 月前3
XDNN TVM - Nov 2019to access the FPGA runtime APIs© Copyright 2018 Xilinx Registering TVM op in Python at runtime File contrib_xlnx.py: … @tvm.register_func("tvm.accel.accel_fused") def accel_fused(graph_path, output_layout0 码力 | 16 页 | 3.35 MB | 6 月前3
OpenAI 《A practical guide to building agents》@function_tool save_results(output): db.insert({ : output, : datetime.time()}) return "File saved" search_agent = Agent( name= , instructions= tools=[WebSearchTool(),save_results]0 码力 | 34 页 | 7.00 MB | 6 月前3
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