Text-to-Code Generation is a task where we can generate code based on the natural language description. Source: Text-to-code Generation with TensorFlow, 🤗 & MBPPBenchmarks Add a Result These leaderboards are used to track progress in Text-to-Code Generation ...
In the SL stage, we train LLMs using ground-truth parametric sequences, enabling the generation of logically coherent parametric sequences. In the VF stage, we reward parametric sequences that render into visually preferred objects and penalize those that do not, allowing LLMs to learn how ...
CodeT: Code generation with generated tests. In ICLR, 2023a. [3] Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, Dan Bikel, Lukas Blecher, Cristian Canton- Ferrer, Moya Chen, ...
GPT-too: A Language-Model-First Approach for AMR-to-Text-Generation training GPT-2 models to attain state-of-the art AMR-to-text generation. Install Code was tested for Python 3.6 on Linux machines both for x86 and PowerPC architectures. All scripts source an environment script that can be...
The generation configuration allows for setting up the output production of a model. A complete description of the manageable parameters can be found at the following GitHub address. Internally, these parameters are defined within the TGenerationConfig class, which extends TJSONParam in the Gemini.Ch...
At the annual Baidu World Conference, CEO Robin Li introduced I-RAG, a text-to-image technology that leverages Baidu's search capabilities to address the "hallucination" issue, referring to the generation of images that deviate from the input text or contain non-existent elements. ...
GPT-2Code generation, as a very hot application area of deep learning models for text, consists of two different fields: code-to-code and text-to-code. A recent approach, GraphCodeBERT uses code graph, which is called data flow, and showed good performance improvement. The base model ...
unique characters:", n_unique_chars) # dictionary that converts characters to integers char2int = {c: i for i, c in enumerate(vocab)} # dictionary that converts integers to characters int2char = {i: c for i, c in enumerate(vocab)} # save these dictionaries for later generation ...
There’s life beyond UML. If you’re more into ER than UML (and I agree thatER has some good points),QuickDatabaseDiagramsoffers a textual notation to draw ER diagrams. Also, Umple (described above) supports the generation of ER visualizations. ...
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