ilintar/Agents-A1-GGUF overview
Optimized with my branch's custom auto tensor type , custom made recipes for 3.77, 4.02 and 4.27 bpw element gamma=0.25, tuned for MoE — recovers the bits that…
Runs locally from ~15.21 GB disk (16 GB VRAM class GPUs with llama.cpp / guIDE).
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Model Details
Model README
---
license: apache-2.0
base_model:
- InternScience/Agents-A1
---
Optimized with my branch's custom auto-tensor-type, custom-made recipes for 3.77, 4.02 and 4.27 bpw
(element-gamma=0.25, tuned for MoE — recovers the bits that plain size-weighting over-spends on the
rarely-activated experts).
Since HF doesn't recognize custom bpw tags, I've tagged them with:
- IQ3_M: 3.77bpw
- Q3_K_M: 4.02bpw
- IQ4_XS: 4.27bpw
Note that the quant types are only aliases for the size and do not correspond to the actual quant types used.
Converted with --no-mtp, so the multi-token-prediction head is excluded — these are standard-inference GGUFs.
Run ilintar/Agents-A1-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models