GLM-4.7 API vs TinyLlama
Overview
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CLI (Node.js)
Manual
Detailed Comparison
It aims to pre-train a 1.1 billion parameter language model on 3 trillion tokens of text data. It is compact with only 1.1B parameters. This compactness allows it to cater to a multitude of applications demanding a restricted computation and memory footprint. | Build smarter coding agents with the GLM-4.7 API, featuring multilingual coding, terminal tasks, and think-before-act reasoning. |
1.1 billion parameter language model;
Trained on 3 trillion tokens of text data;
Uses the same architecture and tokenizer as Llama 2;
Compact and fast | Model Library, Serverless Inference, Dedicated Endpoint, Canopy Wave Chat, NVIDIA GB200 NVL72 |
Statistics | |
GitHub Stars 8.8K | GitHub Stars - |
GitHub Forks 572 | GitHub Forks - |
Stacks 0 | Stacks 0 |
Followers 2 | Followers 1 |
Votes 0 | Votes 1 |
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