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paumkim/zomi-qlora-v1
zomi-qlora-v1 is a text generation model from paumkim. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
A Qwen 2.5 3B fine-tuned on Zomi (Zou) language text using QLoRA (rank 128).
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From the Hugging Face model README
A Qwen 2.5 3B fine-tuned on Zomi (Zou) language text using QLoRA (rank 128).
This model can generate and understand Zomi text. It is the first publicly available language model for the Zomi language (spoken by ~500,000 people across Myanmar, India, and Bangladesh).
This is a continued pretraining / language adaptation model. It speaks Zomi but does not yet follow directions. Phase 2 (instruction tuning) will add command-following ability.
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "paumkim/zomi-qlora-v1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
model_name,
device_map="auto",
torch_dtype="auto",
)
# Generate Zomi text
prompt = "Pasian in hong it"
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=100)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
This model is a QLoRA adapter (rank 128) on top of Qwen 2.5 3B. You can load it and fine-tune further:
from peft import PeftModel
base = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-3B", device_map="auto")
model = PeftModel.from_pretrained(base, model_name)
# Continue training with your own Zomi data
| Parameter | Value |
|---|---|
| Base model | Qwen 2.5 3B |
| Method | QLoRA (rank 128, alpha 256) |
| Trainable params | 239M (7.2% of base) |
| Data | ~54,000 chunks of Zomi text from public sources |
| Hardware | NVIDIA A100 80GB |
| GPU hours | ~20 hours |
The model was trained on a corpus of Zomi text collected from public sources including:
All data was collected with respect for community ownership of the Zomi language.
Most AI models do not support Zomi. The Zomi language has ~500,000 speakers but zero commercial AI representation. This model is an attempt to change that — built by a Zomi speaker, for Zomi speakers.
Instruction fine-tuning is in progress. The Phase 2 model will follow commands in Zomi, enabling translation,问答, content generation, and more.
MIT — free to use, modify, and distribute. We believe the Zomi language should belong to its community, not to any company.