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Survivor-v1-2B
theprint/Survivor-v1-2B
Survivor-v1-2B is a text generation model from theprint. Use it when you need the model to write or continue text. It is set up for transformers.
A fine-tuned version of unsloth/Qwen3.5-2B trained on Off Grid Survival sharegpt data using Auto-SFT — an automated hyperparameter search and supervised fine-tuning pipeline.
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At a glance
- Task
- Text Generation
- Library
- transformers
- Model type
- qwen3_5_text
- Access
- Public
- Created
- Jul 10, 2026
- Updated
- Jul 20, 2026
- SHA
- 42083183
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Base models
Model card
From the Hugging Face model README
Survivor-v1-2B
A fine-tuned version of unsloth/Qwen3.5-2B trained on Off Grid Survival 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 Off Grid Survival 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 | data/Off-Grid-Survival-sharegpt.json |
| Fine-tuning epochs | 2 |
| Fine-tuning date | 2026-07-10 |
| Fine-tuning method | LoRA (merged to full 16-bit) |
Training Hyperparameters
LoRA
| Parameter | Value |
|---|---|
r | 16 |
alpha | 64 |
dropout | 0.06 |
target_modules | ['q_proj', 'v_proj'] |
Training
| Parameter | Value |
|---|---|
learning_rate | 2e-05 |
batch_size | 4 |
gradient_accumulation_steps | 4 |
warmup_ratio | 0.03 |
max_seq_length | 2048 |
quantization | none |
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("theprint/Survivor-v1-2B")
tokenizer = AutoTokenizer.from_pretrained("theprint/Survivor-v1-2B")
- Task
- Text Generation
- Library
- transformers
- Type
- qwen3_5_text
- Languages
- en
- Created
- Jul 10, 2026
- Updated
- Jul 20, 2026