commit bbd8b9ca991f003a287048bfc21adb917f7b435d Author: ModelHub XC Date: Fri Jun 5 11:42:16 2026 +0800 初始化项目，由ModelHub XC社区提供模型 Model: israel/LLAMA-Walia-II Source: Original Platform diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..a6344aa --- /dev/null +++ b/.gitattributes @@ -0,0 +1,35 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx 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-0,0 +1,82 @@ +--- +license: apache-2.0 +datasets: +- EthioNLP/Amharic_Instruction_dataset +- iocuydi/amharic-alpaca +language: +- am +- en +--- +# [Walia-LLM: Enhancing Amharic-LLaMA by Integrating Task-Specific and Generative Datasets](https://aclanthology.org/2024.findings-emnlp.25/) - combined data + + + + +## Model Details + +- Base model: LLaMA-2 +- Fine-tuning method: Supervised fine-tuning (SFT) using LoRA +- Language: Amharic +- Tasks: + - Sentiment analysis + - Question answering + - Named entity recognition + - News classification + - Summarization + - Machine translation + - Poem/story/lyrics generation + - Spelling correction + +## Training Data + +The model was trained on a custom instruction dataset derived from: +- Existing NLP benchmarks (e.g., AfriSenti, AmharicQA, MasakhaNER, MasakhaNews, XL-Sum) +- Manually collected generative datasets (e.g., religious lyrics, stories, poems) +- Translated instruction datasets (e.g., Alpaca, Dolly) + +See [EthioNLP/walia-amharic-instructions](https://huggingface.co/datasets/EthioNLP/walia-amharic-instructions) for the dataset used. + +## Intended Use + +This model is intended for: +- Research on instruction tuning in low-resource languages +- Generative NLP tasks in Amharic +- Evaluating multilingual LLM capabilities + +## Limitations + +- Some generative outputs may be verbose or imprecise. +- Limited understanding of highly specific Amharic poetic or lyrical structures. +- Spell correction and NER performance is still under exploration. + +## Example Usage + +```python +from transformers import AutoTokenizer, AutoModelForCausalLM + +model = AutoModelForCausalLM.from_pretrained("israel/LLAMA-Walia-II") +tokenizer = AutoTokenizer.from_pretrained("israel/LLAMA-Walia-II") + +prompt = "ስለ አማርኛ ቋንቋ መግለጫ አቅርብ።" +inputs = tokenizer(prompt, return_tensors="pt") +outputs = model.generate(**inputs, max_new_tokens=100) +print(tokenizer.decode(outputs[0], skip_special_tokens=True)) +``` + +## Citation + +```bibtex +@inproceedings{azime-etal-2024-walia, + title = "Walia-{LLM}: Enhancing {A}mharic-{LL}a{MA} by Integrating Task-Specific and Generative Datasets", + author = "Azime, Israel Abebe and Tonja, Atnafu Lambebo and Belay, Tadesse Destaw and Fuge, Mitiku Yohannes and Wassie, Aman Kassahun and Jada, Eyasu Shiferaw and Chanie, Yonas and Sewunetie, Walelign Tewabe and Yimam, Seid Muhie", + editor = "Al-Onaizan, Yaser and Bansal, Mohit and Chen, Yun-Nung", + booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2024", + month = nov, + year = "2024", + address = "Miami, Florida, USA", + publisher = "Association for Computational Linguistics", + url = "https://aclanthology.org/2024.findings-emnlp.25/", + doi = "10.18653/v1/2024.findings-emnlp.25", + pages = "432--444" +} +``` \ No newline at end of file diff --git a/added_tokens.json b/added_tokens.json new file mode 100644 index 0000000..ae8cfd2 --- /dev/null +++ b/added_tokens.json @@ -0,0 +1,3 @@ +{ 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