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theprint/SelfHelp-v1-2B-GGUF overview

SelfHelp v1 2B GGUF A fine tuned version of unsloth/Qwen3.5 2B https://huggingface.co/unsloth/Qwen3.5 2B trained on theprint SelfHelp ShareGPT data using Auto …

transformersgguffine-tunedlorasftauto-sftendataset:theprint/SelfHelp-ShareGPTbase_model:unsloth/Qwen3.5-2Bbase_model:adapter:unsloth/Qwen3.5-2Bendpoints_compatibleregion:usconversational

Runs locally from ~637.3 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Repository Files & Downloads

17 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
SelfHelp-v1-2B-GGUF-BF16.ggufGGUFBF163.63 GBDownload
SelfHelp-v1-2B-GGUF-IQ4_NL.ggufGGUFIQ4_NL1.18 GBDownload
SelfHelp-v1-2B-GGUF-IQ4_XS.ggufGGUFIQ4_XS1.15 GBDownload
SelfHelp-v1-2B-GGUF-Q2_K.ggufGGUFQ2_K944.6 MBDownload
SelfHelp-v1-2B-GGUF-Q3_K_L.ggufGGUFQ3_K_L1.11 GBDownload
SelfHelp-v1-2B-GGUF-Q3_K_M.ggufGGUFQ3_K_M1.05 GBDownload
SelfHelp-v1-2B-GGUF-Q3_K_S.ggufGGUFQ3_K_S997.9 MBDownload
SelfHelp-v1-2B-GGUF-Q4_K_M.ggufGGUFQ4_K_M1.22 GBDownload
SelfHelp-v1-2B-GGUF-Q4_K_S.ggufGGUFQ4_K_S1.16 GBDownload
SelfHelp-v1-2B-GGUF-Q5_K_M.ggufGGUFQ5_K_M1.35 GBDownload
SelfHelp-v1-2B-GGUF-Q5_K_S.ggufGGUFQ5_K_S1.32 GBDownload
SelfHelp-v1-2B-GGUF-Q6_K.ggufGGUFQ6_K1.50 GBDownload
SelfHelp-v1-2B-GGUF-Q8_0.ggufGGUFQ8_01.93 GBDownload
SelfHelp-v1-2B-GGUF-TQ2_0.ggufGGUFGGUF762.9 MBDownload
mmproj-BF16.ggufGGUFBF16640.3 MBDownload
mmproj-F16.ggufGGUFF16637.3 MBDownload
mmproj-F32.ggufGGUFF321.23 GBDownload

Model Details

Model IDtheprint/SelfHelp-v1-2B-GGUF
Authortheprint
Pipeline
License
Base modelunsloth/Qwen3.5-2B
Last modified2026-07-21T10:59:05.000Z

Model README

---

base_model: unsloth/Qwen3.5-2B

datasets:

  • theprint/SelfHelp-ShareGPT

tags:

  • fine-tuned
  • lora
  • sft
  • auto-sft

language:

  • en

library_name: transformers

---

SelfHelp-v1-2B (GGUF)

A fine-tuned version of unsloth/Qwen3.5-2B trained on theprint SelfHelp ShareGPT data using Auto-SFT — an automated hyperparameter search and supervised fine-tuning pipeline.

The base model was adapted to follow the style and content of the theprint SelfHelp ShareGPT dataset. Expect improved performance on tasks similar to those represented in the training data.

Model Details

| Property | Value |

|---|---|

| Base model | unsloth/Qwen3.5-2B |

| Training data | theprint/SelfHelp-ShareGPT |

| Fine-tuning epochs | 2 |

| Fine-tuning date | 2026-07-20 |

| Fine-tuning method | LoRA (merged to full 16-bit) |

Training Hyperparameters

LoRA

| Parameter | Value |

|---|---|

| r | 64 |

| alpha | 64 |

| dropout | 0.03 |

| target_modules | ['q_proj', 'v_proj', 'k_proj', 'o_proj'] |

Training

| Parameter | Value |

|---|---|

| learning_rate | 1e-05 |

| batch_size | 2 |

| gradient_accumulation_steps | 4 |

| warmup_ratio | 0.05 |

| max_seq_length | 512 |

| quantization | none |

GGUF Files

These quantized GGUF files can be used directly with llama.cpp, Ollama, LM Studio, and other compatible runtimes.

| File | Description |

|---|---|

| SelfHelp-v1-2B-GGUF-BF16.gguf | BF16 |

| SelfHelp-v1-2B-GGUF-Q8_0.gguf | 8-bit — near-lossless, larger file |

| SelfHelp-v1-2B-GGUF-Q6_K.gguf | 6-bit — high quality |

| SelfHelp-v1-2B-GGUF-Q5_K_M.gguf | 5-bit medium — good quality/size balance |

| SelfHelp-v1-2B-GGUF-Q5_K_S.gguf | Q5_K_S |

| SelfHelp-v1-2B-GGUF-Q4_K_M.gguf | 4-bit medium — recommended for most use cases |

| SelfHelp-v1-2B-GGUF-Q4_K_S.gguf | Q4_K_S |

| SelfHelp-v1-2B-GGUF-Q3_K_L.gguf | Q3_K_L |

| SelfHelp-v1-2B-GGUF-Q3_K_M.gguf | Q3_K_M |

| SelfHelp-v1-2B-GGUF-Q3_K_S.gguf | Q3_K_S |

| SelfHelp-v1-2B-GGUF-Q2_K.gguf | 2-bit — smallest size, lowest quality |

| SelfHelp-v1-2B-GGUF-IQ4_XS.gguf | IQ4_XS |

| SelfHelp-v1-2B-GGUF-IQ4_NL.gguf | IQ4_NL |

| SelfHelp-v1-2B-GGUF-TQ2_0.gguf | TQ2_0 |

---

Generated by Auto-SFT

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