| | --- |
| | license: apache-2.0 |
| | language: |
| | - en |
| | base_model: |
| | - prithivMLmods/FastThink-0.5B-Tiny |
| | pipeline_tag: text-generation |
| | library_name: transformers |
| | tags: |
| | - text-generation-inference |
| | --- |
| | # **FastThink-0.5B-Tiny-GGUF** |
| |
|
| | > 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. |
| |
|
| | ## Model Files |
| |
|
| | | File | Size | Description | |
| | |------|------|-------------| |
| | | README.md | 31 Bytes | Project documentation | |
| | | config.json | 31 Bytes | Model configuration | |
| | | .gitattributes | 2.39 kB | Git attributes configuration | |
| | | FastThink-0.5B-Tiny.BF16.gguf | 994 MB | BFloat16 quantized model | |
| | | FastThink-0.5B-Tiny.F16.gguf | 994 MB | Float16 quantized model | |
| | | FastThink-0.5B-Tiny.F32.gguf | 1.98 GB | Float32 full precision model | |
| | | FastThink-0.5B-Tiny.Q2_K.gguf | 339 MB | 2-bit K-quantized model | |
| | | FastThink-0.5B-Tiny.Q3_K_L.gguf | 369 MB | 3-bit K-quantized model (Large) | |
| | | FastThink-0.5B-Tiny.Q3_K_M.gguf | 355 MB | 3-bit K-quantized model (Medium) | |
| | | FastThink-0.5B-Tiny.Q3_K_S.gguf | 338 MB | 3-bit K-quantized model (Small) | |
| | | FastThink-0.5B-Tiny.Q4_K_M.gguf | 398 MB | 4-bit K-quantized model (Medium) | |
| | | FastThink-0.5B-Tiny.Q4_K_S.gguf | 385 MB | 4-bit K-quantized model (Small) | |
| | | FastThink-0.5B-Tiny.Q5_K_M.gguf | 420 MB | 5-bit K-quantized model (Medium) | |
| | | FastThink-0.5B-Tiny.Q5_K_S.gguf | 413 MB | 5-bit K-quantized model (Small) | |
| | | FastThink-0.5B-Tiny.Q6_K.gguf | 506 MB | 6-bit K-quantized model | |
| | | FastThink-0.5B-Tiny.Q8_0.gguf | 531 MB | 8-bit quantized model | |
| | |
| | ## Quants Usage |
| | |
| | (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) |
| | |
| | Here is a handy graph by ikawrakow comparing some lower-quality quant |
| | types (lower is better): |
| | |
| |  |
