Sorjin1 7B
Sorjîn1-7B is a Kurdish Kurmanji language model produced by continually pretraining Qwen/Qwen2.5-7B on academic theses written in Kurdish Kurmanji.
Model source
- Kind
- Other
- File size
- 1.02–4.59 GB
- Base model
- Qwen/Qwen2.5-7B
- Version
- vRevision 97102ee
- Updated
- Sep 26, 2026
- Downloads
- 10
- Source
- Hugging Face
Source description
Sorjîn1-7B
Sorjîn1-7B is a Kurdish Kurmanji language model produced by continually pretraining Qwen/Qwen2.5-7B on academic theses written in Kurdish Kurmanji.
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained(
"muzaffercky/Sorjin1-7B",
torch_dtype="bfloat16",
device_map="auto",
)
tokenizer = AutoTokenizer.from_pretrained("muzaffercky/Sorjin1-7B")
inputs = tokenizer("Zimanê kurdî zimanekî", return_tensors="pt").to(model.device)
output = model.generate(**inputs, max_new_tokens=100)
print(tokenizer.decode(output[0], skip_special_tokens=True))
Evaluation
| Model | Eval Loss | Perplexity |
|---|---|---|
| Qwen/Qwen2.5-7B (base) | 3.42 | 30.57 |
| Sorjîn1-7B | 1.86 | 6.42 |
5× perplexity reduction after a single epoch of continual pretraining.
Training
- Base model: Qwen/Qwen2.5-7B
- Dataset: muzaffercky/kurdish-kurmanji-theses — 389 academic theses, 57.6 MB of cleaned Kurmanji text
- Method: QLoRA continual pretraining (4-bit NF4 quantization during training, merged to bfloat16)
- LoRA rank: 64, alpha: 128, target modules: all attention and MLP projections
- Sequence length: 2048 tokens
- Epochs: 1
- Hardware: 1× NVIDIA RTX 4090
Intended Use
This is a base model — it is not instruction-tuned. It is intended for:
- Further fine-tuning on Kurdish downstream tasks
- Merging with instruction-tuned models (see Sorjîn1-7B-Instruct)
- Kurdish language research
Limitations
- Trained on academic theses only — language style is formal and academic
- Single epoch training — further pretraining on broader Kurdish data would improve general language coverage
- Not suitable for direct use as a chat assistant — use Sorjîn1-7B-Instruct instead
Model Family
| Model | Description |
|---|---|
| Sorjîn1-LoRA | Raw LoRA adapter weights |
| Sorjîn1-7B (this model) | Continually pretrained base model |
| Sorjîn1-7B-Instruct | Merged with Qwen2.5-7B-Instruct |
Sources
1 source
Sources
1 sourceVerified Sep 7
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Model artifacts
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Model artifacts
4 artifactsmodel-00001-of-00004.safetensors
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Source excerpts
2 excerpts--- language: - ku - kmr base_model: Qwen/Qwen2.5-7B tags: - kurdish - kurmanji - continual-pretraining - lora - qwen2.5 license: apache-2.0 datasets: - muzaffercky/kurdish-kurmanji-theses --- # Sorjîn1-7B Sorjîn1-7B is a Kurdish Kurmanji language model produced by continually pretraining [Qwen/Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B) on academic theses written in Kurdish Kurmanji. ## Usage ```python from transformers import AutoModelForCausalLM, AutoTokenizer model = AutoModelForCausalLM.from_pretrained( "muzaffercky/Sorjin1-7B", torch_dtype="bfloat16", device_map="auto", ) tokenizer = AutoTokenizer.from_pretrained("muzaffercky/Sorjin1-7B") inputs = tokenizer("Zimanê kurdî zimanekî", return_tensors="pt").to(model.device) output = model.generate(**inputs, max_new_tokens=100) print(tokenizer.decode(output[0], skip_special_tokens=True)) ``` ## Evaluation | Model | Eval Loss | Perplexity | |-------|-----------|------------| | Qwen/Qwen2.5-7B (base) | 3.42 | 30.57 | | Sorjîn1-7B | 1.86 | 6.42 | 5× perplexity reduction after a single epoch of continual pretraining. ## Training - **Base model:** [Qwen/Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B) - **Dataset:** [muzaffercky/kurdish-kurmanji-theses](https://huggingface.co/datasets/muzaffercky/kurdish-kurmanji-theses) — 389 academic theses, 57.6 MB of cleaned Kurmanji text - **Method:** QLoRA continual pretraining (4-bit NF4 quantization during training, merged to bfloat16) - **LoRA rank:** 64, alpha: 128, target modules: all attention and MLP projections - **Sequence length:** 2048 tokens - **Epochs:** 1 - **Hardware:** 1× NVIDIA RTX 4090 ## Intended Use This is a **base model** — it is not instruction-tuned. It is intended for: - Further fine-tuning on Kurdish downstream tasks - Merging with instruction-tuned models (see [Sorjîn1-7B-Instruct](https://huggingface.co/muzaffercky/Sorjin1-7B-Instruct)) - Kurdish language research ## Limitations - Trained on academic theses only — language style is formal and academic - Single epoch training — further pretraining on broader Kurdish data would improve general language coverage - Not suitable for direct use as a chat assistant — use Sorjîn1-7B-Instruct instead ## Model Family | Model | Description | |-------|-------------| | [Sorjîn1-LoRA](https://huggingface.co/muzaffercky/Sorjin1-LoRA) | Raw LoRA adapter weights | | Sorjîn1-7B (...
Source context: 10 downloads · 0 likes · Repo muzaffercky/Sorjin1-7B
