Open multilingual multimodal chat LMs for dialogue, reasoning, and rumination
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The GLM-4 series offers open-source, multilingual, multimodal chat Large Language Models (LLMs) designed for dialogue, reasoning, and agent tasks. Targeting researchers and developers, these models provide competitive performance against leading proprietary models, with a focus on user-friendly local deployment and extended context capabilities.
How It Works
The GLM-4 models are built on a foundation of extensive pre-training (up to 15T tokens) incorporating reasoning-focused synthetic data. Post-training employs human preference alignment for dialogue, alongside techniques like rejection sampling and reinforcement learning to enhance instruction following, code generation, and function calling. Specialized variants like GLM-Z1-Rumination-32B-0414 utilize scaled end-to-end reinforcement learning with rubric-graded responses and tool usage for complex, open-ended problem-solving.
Quick Start & Requirements
transformers
and torch
. Example fine-tuning command: cd finetune && pip install -r ../inference/requirements.txt && pip install -r requirements.txt && python finetune.py data/AdvertiseGen/ THUDM/GLM-4-9B-0414 configs/lora.yaml
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Maintenance & Community
Licensing & Compatibility
Limitations & Caveats
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