初始化项目，由ModelHub XC社区提供模型

Model: paumkim/zomi-qlora-v1
Source: Original Platform

README.md

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+---
+license: mit
+library_name: transformers
+tags:
+- zomi
+- qwen
+- qlora
+- low-resource-language
+- text-generation
+pipeline_tag: text-generation
+base_model: Qwen/Qwen2.5-3B
+language:
+- zom
+- en
+---
+
+# Zomi QLoRA v1 — Zomi Language Model
+
+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).
+
+## What This Model Can Do
+
+- Generate coherent Zomi text
+- Complete Zomi sentences and passages
+- Understand Zomi grammar, vocabulary, and structure
+- Serve as a foundation for further fine-tuning
+
+## What This Model Cannot Do (Yet)
+
+- Follow instructions or commands (Phase 2 — instruction fine-tuning — is in progress)
+- Translate between Zomi and English on demand
+- Hold conversations
+
+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.
+
+## How to Use
+
+```python
+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))
+```
+
+## Fine-Tune It Yourself
+
+This model is a QLoRA adapter (rank 128) on top of Qwen 2.5 3B. You can load it and fine-tune further:
+
+```python
+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
+```
+
+## Training Details
+
+| 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 |
+
+## Dataset
+
+The model was trained on a corpus of Zomi text collected from public sources including:
+- Zomi literature and publications
+- Community-contributed content
+- Public domain religious texts in Zomi
+
+All data was collected with respect for community ownership of the Zomi language.
+
+## Why This Model Exists
+
+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.
+
+## Phase 2 (Coming)
+
+Instruction fine-tuning is in progress. The Phase 2 model will follow commands in Zomi, enabling translation,问答, content generation, and more.
+
+## License
+
+MIT — free to use, modify, and distribute. We believe the Zomi language should belong to its community, not to any company.