44 lines
1.9 KiB
Markdown
44 lines
1.9 KiB
Markdown
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---
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license: apache-2.0
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language:
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- en
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base_model:
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- prithivMLmods/FastThink-0.5B-Tiny
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pipeline_tag: text-generation
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library_name: transformers
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tags:
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- text-generation-inference
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---
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# **FastThink-0.5B-Tiny-GGUF**
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> FastThink-0.5B-Tiny is a reasoning-focused model based on Qwen2.5. They have released a range of base language models and instruction-tuned language models, spanning from 0.5 billion to 72 billion parameters.
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## Model Files
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| File | Size | Description |
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|------|------|-------------|
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| README.md | 31 Bytes | Project documentation |
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| config.json | 31 Bytes | Model configuration |
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| .gitattributes | 2.39 kB | Git attributes configuration |
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| FastThink-0.5B-Tiny.BF16.gguf | 994 MB | BFloat16 quantized model |
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| FastThink-0.5B-Tiny.F16.gguf | 994 MB | Float16 quantized model |
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| FastThink-0.5B-Tiny.F32.gguf | 1.98 GB | Float32 full precision model |
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| FastThink-0.5B-Tiny.Q2_K.gguf | 339 MB | 2-bit K-quantized model |
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| FastThink-0.5B-Tiny.Q3_K_L.gguf | 369 MB | 3-bit K-quantized model (Large) |
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| FastThink-0.5B-Tiny.Q3_K_M.gguf | 355 MB | 3-bit K-quantized model (Medium) |
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| FastThink-0.5B-Tiny.Q3_K_S.gguf | 338 MB | 3-bit K-quantized model (Small) |
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| FastThink-0.5B-Tiny.Q4_K_M.gguf | 398 MB | 4-bit K-quantized model (Medium) |
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| FastThink-0.5B-Tiny.Q4_K_S.gguf | 385 MB | 4-bit K-quantized model (Small) |
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| FastThink-0.5B-Tiny.Q5_K_M.gguf | 420 MB | 5-bit K-quantized model (Medium) |
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| FastThink-0.5B-Tiny.Q5_K_S.gguf | 413 MB | 5-bit K-quantized model (Small) |
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| FastThink-0.5B-Tiny.Q6_K.gguf | 506 MB | 6-bit K-quantized model |
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| FastThink-0.5B-Tiny.Q8_0.gguf | 531 MB | 8-bit quantized model |
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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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