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ECE ILAB Q1 by paulml

By paulml · 15 downloads
HF Repo ↗ Copy URL

ECE ILAB Q1 is an open-source language model by paulml. Features: 72b LLM, VRAM: 77.8GB, Context: 32K, License: other, Quantized, Instruction-Based, Merged, LLM Explorer Score: 0.25.

  Merged Model Cognitivecomputations/dolphin-...   Conversational   Endpoints compatible   Instruct   Model-index   Q1   Quantized   Qwen/qwen2-72b-instruct   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/paulml/ECE-ILAB-Q1 

ECE ILAB Q1 Parameters and Internals

Model Type 
text-generation
Additional Notes 
merge-qwen2-72B is a merge of the Qwen/Qwen2-72B-Instruct and cognitivecomputations/dolphin-2.9.2-qwen2-72b models using mergekit.
LLM NameECE ILAB Q1
Repository 🤗https://huggingface.co/paulml/ECE-ILAB-Q1 
Merged ModelYes
Model Size72b
Required VRAM77.8 GB
Updated2026-07-28
Maintainerpaulml
Model Typeqwen2
Instruction-BasedYes
Model Files  1.3 GB: 1-of-83   2.5 GB: 2-of-83   1.9 GB: 3-of-83   1.6 GB: 4-of-83   1.6 GB: 5-of-83   1.8 GB: 6-of-83   1.9 GB: 7-of-83   1.6 GB: 8-of-83   1.8 GB: 9-of-83   1.8 GB: 10-of-83   1.9 GB: 11-of-83   1.9 GB: 12-of-83   1.6 GB: 13-of-83   1.6 GB: 14-of-83   1.8 GB: 15-of-83   1.9 GB: 16-of-83   1.6 GB: 17-of-83   1.8 GB: 18-of-83   1.8 GB: 19-of-83   1.9 GB: 20-of-83   1.9 GB: 21-of-83   1.6 GB: 22-of-83   1.6 GB: 23-of-83   1.8 GB: 24-of-83   1.9 GB: 25-of-83   1.6 GB: 26-of-83   1.8 GB: 27-of-83   1.8 GB: 28-of-83   1.9 GB: 29-of-83   1.9 GB: 30-of-83   1.6 GB: 31-of-83   1.6 GB: 32-of-83   1.8 GB: 33-of-83   1.9 GB: 34-of-83   1.6 GB: 35-of-83   1.8 GB: 36-of-83   1.8 GB: 37-of-83   1.9 GB: 38-of-83   1.9 GB: 39-of-83   1.6 GB: 40-of-83   1.6 GB: 41-of-83   1.8 GB: 42-of-83   1.9 GB: 43-of-83   1.6 GB: 44-of-83
Quantization Typeq1
Model ArchitectureQwen2ForCausalLM
Licenseother
Context Length32768
Model Max Length32768
Transformers Version4.41.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than paulml/ECE-ILAB-Q1.