Hercules Qwen1.5 14B by M4-ai

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  Autotrain compatible   Conversational Dataset:locutusque/hercules-v4...   En   Endpoints compatible   Qwen2   Region:us   Safetensors   Sharded   Tensorflow

Hercules Qwen1.5 14B Benchmarks

Hercules Qwen1.5 14B (M4-ai/Hercules-Qwen1.5-14B)
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Hercules Qwen1.5 14B Parameters and Internals

Model Type 
NLP, code generation
Use Cases 
Applications:
General purpose assistant, question answering, chain-of-thought
Considerations:
Users should be made aware of the risks, biases, and limitations of the model.
Additional Notes 
The model is fine-tuned using 700,000 examples from the Hercules-v4 dataset. It employs bf16 non-mixed precision training regime. Contributions were made by @Tonic, @aloobun, @fhai50032, and @Locutusque.
Supported Languages 
en (high proficiency), zh (unknown proficiency)
Training Details 
Data Sources:
https://huggingface.co/datasets/Locutusque/hercules-v4.0
Context Length:
1024
Hardware Used:
8 Kaggle TPUs
LLM NameHercules Qwen1.5 14B
Repository ๐Ÿค—https://huggingface.co/M4-ai/Hercules-Qwen1.5-14B 
Model Size14b
Required VRAM28.4 GB
Updated2025-09-23
MaintainerM4-ai
Model Typeqwen2
Model Files  1.9 GB: 1-of-15   1.9 GB: 2-of-15   1.9 GB: 3-of-15   1.9 GB: 4-of-15   1.9 GB: 5-of-15   1.9 GB: 6-of-15   1.9 GB: 7-of-15   1.9 GB: 8-of-15   1.9 GB: 9-of-15   1.9 GB: 10-of-15   1.9 GB: 11-of-15   1.9 GB: 12-of-15   1.9 GB: 13-of-15   1.9 GB: 14-of-15   1.8 GB: 15-of-15
Supported Languagesen
Model ArchitectureQwen2ForCausalLM
Licenseother
Context Length32768
Model Max Length32768
Transformers Version4.39.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124