RaspizdAI/debil-1.5-GGUF overview
🚀 debil 1.5 GGUF debil 1.5 in GGUF format, available in multiple quantization levels. Technical Specifications: Total Parameters: 46,538,400 ~46.5M Vocabulary…
Runs locally from ~39.1 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
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Model Details
Model README
---
license: mit
tags:
- debil
---
🚀 debil-1.5 GGUF
debil-1.5 in GGUF format, available in multiple quantization levels.
Technical Specifications:
- Total Parameters: 46,538,400 (~46.5M)
- Vocabulary Size: 50,257
- Embedding Dimensions: 480
- Hidden Layers: 8
- Attention Heads: 8
- Head Dimension: 60
- Format: GGUF
Available Quantizations:
| Quantization | File |
| ---------------- | ------------------------ |
| FP16 | debil-1.5-fp16.gguf |
| Q8_0 | debil-1.5-Q8_0.gguf |
| Q4_K_M | debil-1.5-Q4_K_M.gguf |
| IQ2_XXS | debil-1.5-IQ2_XXS.gguf |
| IQ1_S | debil-1.5-IQ1_S.gguf |
Quantization Details:
- FP16 — unquantized version with FP16 weights.
- Q8_0 — 8-bit quantization with minimal quality loss.
- Q4_K_M — 4-bit K-quants offering a good size/quality balance.
- IQ2_XXS — ultra-low-bit importance quantization.
- IQ1_S — extremely aggressive 1-bit-class quantization for minimal file size.
Run RaspizdAI/debil-1.5-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models