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Building on HF
77.8
TFLOPS
Ed Addario
PRO
eaddario
21
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128 followers
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36 following
EAddario
AI & ML interests
Finding ways to optimize LLMs' inference performance in resource-constrained environments (e.g. commodity hardware, desktops, laptops, mobiles, edge devices, etc.)
Recent Activity
posted
an
update
5 days ago
Experimental global target bits‑per‑weight quantization of openbmb/MiniCPM5-1B and openbmb/MiniCPM5-2B. Unlike standard llama.cpp quantization that rely on fixed type heuristics (e.g., Q4_K_M), the Target BPW approach automatically optimizes per-tensor precision where it matters the most, and produces high quality models that meet a precise global size target. Key Advantages: - VRAM Maximization: Can generate high quality models sized exactly to fit hardware constraints (e.g., fitting the model into exactly 24GB VRAM). - Data-Driven Precision: Quantization mix is determined by actual weight error sensitivity rather than hardcoded rules, often yielding better PPL/KLD size trade-offs. Full benchmarks (PPL, KLD, ARC, GPQA, MMLU, etc.) and methodology in the model's card. https://huggingface.co/eaddario/MiniCPM5-1B-GGUF https://huggingface.co/eaddario/MiniCPM5-2B-GGUF
posted
an
update
6 days ago
Experimental global target bits‑per‑weight quantization of XHToken/Spark-X2.5-1.7B and XHToken/Spark-X2.5-4B. Unlike standard llama.cpp quantization that rely on fixed type heuristics (e.g., Q4_K_M), the Target BPW approach automatically optimizes per-tensor precision where it matters the most, and produces high quality models that meet a precise global size target. Key Advantages: - VRAM Maximization: Can generate high quality models sized exactly to fit hardware constraints (e.g., fitting the model into exactly 24GB VRAM). - Data-Driven Precision: Quantization mix is determined by actual weight error sensitivity rather than hardcoded rules, often yielding better PPL/KLD size trade-offs. Full benchmarks (PPL, KLD, ARC, GPQA, MMLU, etc.) and methodology in the model's card. https://huggingface.co/eaddario/Spark-X2.5-1.7B-GGUF https://huggingface.co/eaddario/Spark-X2.5-4B-GGUF
updated
a model
6 days ago
eaddario/Spark-X2.5-1.7B-GGUF
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liked
2 models
about 1 year ago
dphn/Dolphin-Mistral-24B-Venice-Edition
Text Generation
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24B
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Updated
Jun 12
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333k
•
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702
marcelbinz/Llama-3.1-Centaur-70B
Text Generation
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71B
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Updated
Jul 1, 2025
•
175
•
84
liked
5 datasets
over 1 year ago
nvidia/OpenMathInstruct-2
Viewer
•
Updated
Nov 25, 2024
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22M
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136k
•
254
Multilingual-Multimodal-NLP/McEval-Instruct
Viewer
•
Updated
Jun 12, 2024
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35.9k
•
246
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39
ise-uiuc/Magicoder-Evol-Instruct-110K
Viewer
•
Updated
Dec 28, 2023
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111k
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40k
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188
OpenCoder-LLM/opc-sft-stage2
Viewer
•
Updated
Nov 24, 2024
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436k
•
6.27k
•
105
Vezora/Open-Critic-GPT
Viewer
•
Updated
Jul 28, 2024
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55.1k
•
150
•
97
liked
a model
over 1 year ago
MadeAgents/Hammer2.1-7b
8B
•
Updated
Jun 12, 2025
•
207
•
35