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Summarizer-v1-2B-GGUF
theprint/Summarizer-v1-2B-GGUF
Summarizer-v1-2B-GGUF is a machine learning model from theprint. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
A fine-tuned version of unsloth/Qwen3.5-2B trained on theprint Alpaca Docs n Summaries data using Auto-SFT — an automated hyperparameter search and supervised fine-tuning pipeline.
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.gguf21.3 GB · 100%
At a glance
- Library
- transformers
- Access
- Public
- Created
- Jul 12, 2026
- Updated
- Jul 21, 2026
- SHA
- 20e06ede
Base models
Datasets
Model card
From the Hugging Face model README
Summarizer-v1-2B (GGUF)
A fine-tuned version of unsloth/Qwen3.5-2B trained on theprint Alpaca Docs n Summaries 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 Alpaca Docs n Summaries 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/Alpaca-Docs-n-Summaries |
| Fine-tuning epochs | 2 |
| Fine-tuning date | 2026-07-12 |
| Fine-tuning method | LoRA (merged to full 16-bit) |
Training Hyperparameters
LoRA
| Parameter | Value |
|---|---|
r | 64 |
alpha | 64 |
dropout | 0.0 |
target_modules | ['q_proj', 'v_proj', 'k_proj', 'o_proj', 'gate_proj', 'up_proj', 'down_proj'] |
Training
| Parameter | Value |
|---|---|
learning_rate | 1e-05 |
batch_size | 4 |
gradient_accumulation_steps | 1 |
warmup_ratio | 0.05 |
max_seq_length | 2048 |
quantization | none |
GGUF Files
These quantized GGUF files can be used directly with llama.cpp, Ollama, LM Studio, and other compatible runtimes.
| File | Description |
|---|---|
Summarizer-v1-2B-GGUF-BF16.gguf | BF16 |
Summarizer-v1-2B-GGUF-Q8_0.gguf | 8-bit — near-lossless, larger file |
Summarizer-v1-2B-GGUF-Q6_K.gguf | 6-bit — high quality |
Summarizer-v1-2B-GGUF-Q5_K_M.gguf | 5-bit medium — good quality/size balance |
Summarizer-v1-2B-GGUF-Q5_K_S.gguf | Q5_K_S |
Summarizer-v1-2B-GGUF-Q4_K_M.gguf | 4-bit medium — recommended for most use cases |
Summarizer-v1-2B-GGUF-Q4_K_S.gguf | Q4_K_S |
Summarizer-v1-2B-GGUF-Q3_K_L.gguf | Q3_K_L |
Summarizer-v1-2B-GGUF-Q3_K_M.gguf | Q3_K_M |
Summarizer-v1-2B-GGUF-Q3_K_S.gguf | Q3_K_S |
Summarizer-v1-2B-GGUF-Q2_K.gguf | 2-bit — smallest size, lowest quality |
Summarizer-v1-2B-GGUF-IQ4_NL.gguf | IQ4_NL |
Generated by Auto-SFT
- Library
- transformers
- Languages
- en
- Created
- Jul 12, 2026
- Updated
- Jul 21, 2026