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README.md
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pipeline_tag: text-generation
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library_name: transformers
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---
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- en
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pipeline_tag: text-generation
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library_name: transformers
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---
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# **Explora-0.6B-GGUF**
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> Explora-0.6B is a lightweight and efficient general-purpose reasoning model, fine-tuned on Qwen3-0.6B using the first 100,000 entries of the Open-Omega-Explora-2.5M dataset. It is tailored for science and code-focused reasoning tasks, combining symbolic clarity with fluent instruction-following, ideal for exploratory workflows in STEM domains.
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# Model Files
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| File Name | Format | Size | Precision | Description |
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|-----------|---------|------|-----------|-------------|
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| Explora-0.6B.F32.gguf | GGUF | 2.39 GB | 32-bit Float | Full precision model, highest quality |
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| Explora-0.6B.F16.gguf | GGUF | 1.2 GB | 16-bit Float | Half precision, good balance of size and quality |
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| Explora-0.6B.BF16.gguf | GGUF | 1.2 GB | 16-bit BFloat | Brain floating point, optimized for inference |
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| Explora-0.6B.Q8_0.gguf | GGUF | 639 MB | 8-bit Quantized | High quality quantized model |
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| Explora-0.6B.Q6_K.gguf | GGUF | 495 MB | 6-bit Quantized | Very good quality with smaller size |
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| Explora-0.6B.Q5_K_M.gguf | GGUF | 444 MB | 5-bit Quantized (Medium) | Good quality, balanced compression |
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| Explora-0.6B.Q5_K_S.gguf | GGUF | 437 MB | 5-bit Quantized (Small) | Good quality, higher compression |
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| Explora-0.6B.Q4_K_M.gguf | GGUF | 397 MB | 4-bit Quantized (Medium) | Decent quality with good compression |
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| Explora-0.6B.Q4_K_S.gguf | GGUF | 383 MB | 4-bit Quantized (Small) | Decent quality, higher compression |
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| Explora-0.6B.Q3_K_L.gguf | GGUF | 368 MB | 3-bit Quantized (Large) | Lower quality but very compact |
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| Explora-0.6B.Q3_K_M.gguf | GGUF | 347 MB | 3-bit Quantized (Medium) | Lower quality, more compact |
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| Explora-0.6B.Q3_K_S.gguf | GGUF | 323 MB | 3-bit Quantized (Small) | Lower quality, most compact |
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| Explora-0.6B.Q2_K.gguf | GGUF | 296 MB | 2-bit Quantized | Minimal quality, maximum compression |
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## Configuration Files
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| File Name | Size | Description |
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|-----------|------|-------------|
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| config.json | 29 Bytes | Model configuration parameters |
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| .gitattributes | 2.3 kB | Git LFS configuration for large files |
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| README.md | 280 Bytes | Project documentation |
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## Quants Usage
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(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
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Here is a handy graph by ikawrakow comparing some lower-quality quant
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types (lower is better):
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