commit 244293f092b79386b66c12212f26c6ae8cb93ba9 Author: ModelHub XC Date: Mon May 18 17:01:11 2026 +0800 初始化项目，由ModelHub XC社区提供模型 Model: McGill-NLP/AfriqueLlama-8B Source: Original Platform diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..52373fe --- /dev/null +++ b/.gitattributes @@ -0,0 +1,36 @@ +*.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 filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +tokenizer.json filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..120b123 --- /dev/null +++ b/README.md @@ -0,0 +1,207 @@ +--- +library_name: transformers +license: cc-by-4.0 +base_model: meta-llama/Llama-3.1-8B +language: + - af # Afrikaans + - am # Amharic + - ar # Arabic + - en # English + - fr # French + - ha # Hausa + - ig # Igbo + - mg # Malagasy (Plateau) + - ny # Nyanja + - om # Oromo + - pt # Portuguese + - rw # Kinyarwanda + - sn # Shona + - so # Somali + - st # Southern Sotho + - sw # Swahili + - ti # Tigrinya + - tn # Tswana + - xh # Xhosa + - yo # Yoruba + - zu # Zulu +pipeline_tag: text-generation +tags: + - african-languages + - multilingual + - continued-pretraining + - afrique-llm + - llama + - llamafactory +--- + +# AfriqueLlama-8B + +## Model Overview + +**AfriqueLlama-8B** is part of the **AfriqueLLM** suite—a collection of open language models adapted to **20 African languages** through continued pre-training (CPT) on **~26B tokens**. This model is based on [meta-llama/Llama-3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B) and has been specifically adapted for improved performance on African languages while maintaining strong capabilities in high-resource languages. + + +### Key Features + +- **Type**: Causal Language Model (Base/Pre-trained) +- **Base Model**: Llama 3.1 8B +- **Parameters**: 8B +- **Context Length**: 128,000 tokens (native) +- **Training Tokens**: ~26B tokens of carefully curated multilingual data + +## Supported Languages + +AfriqueLlama-8B has been adapted for the following 20 African languages plus 4 high-resource languages: + +| Language | Code | Family | Script | +|----------|------|--------|--------| +| Afrikaans | afr_Latn | Germanic | Latin | +| Swahili | swh_Latn | Bantu | Latin | +| Moroccan Arabic | ary_Arab | Semitic | Arabic | +| Somali | som_Latn | Cushitic | Latin | +| Amharic | amh_Ethi | Semitic | Ethiopic | +| Egyptian Arabic | arz_Arab | Semitic | Arabic | +| Hausa | hau_Latn | Chadic | Latin | +| Kinyarwanda | kin_Latn | Bantu | Latin | +| Zulu | zul_Latn | Bantu | Latin | +| Igbo | ibo_Latn | Volta-Niger | Latin | +| Plateau Malagasy | plt_Latn | Austronesian | Latin | +| Xhosa | xho_Latn | Bantu | Latin | +| Shona | sna_Latn | Bantu | Latin | +| Yoruba | yor_Latn | Volta-Niger | Latin | +| Nyanja | nya_Latn | Bantu | Latin | +| Southern Sotho | sot_Latn | Bantu | Latin | +| Tigrinya | tir_Ethi | Semitic | Ethiopic | +| Tunisian Arabic | aeb_Arab | Semitic | Arabic | +| Oromo | gaz_Latn | Cushitic | Latin | +| Tswana | tsn_Latn | Bantu | Latin | + +**High-resource languages (for catastrophic forgetting mitigation):** English, French, Portuguese, Arabic + +## Training Data + +Our training corpus combines multiple high-quality sources: + +- **African Monolingual Data** (~22.8B tokens): FineWeb2, WURA, and MADLAD-400 +- **Code** (~1B tokens): CornStack-Python for reasoning capabilities +- **Mathematics** (~1B tokens): FineMath-4+ for mathematical understanding +- **Synthetic Data** (~324M tokens): GPT-4.1 translated domain-specific content across 10 domains + +We use **UniMax sampling** to create a balanced distribution, capping high-resource languages at approximately 1B tokens and upsampling lower-resource languages for up to five epochs. + +## Quickstart + +```python +from transformers import AutoModelForCausalLM, AutoTokenizer + +model_name = "McGill-NLP/AfriqueLlama-8B" + +# Load the tokenizer and the model +tokenizer = AutoTokenizer.from_pretrained(model_name) +model = AutoModelForCausalLM.from_pretrained( + model_name, + torch_dtype="auto", + device_map="auto" +) + +# Prepare the model input +prompt = "Bawo ni o ṣe n ṣe?" # Yoruba: "How are you doing?" +inputs = tokenizer(prompt, return_tensors="pt").to(model.device) + +# Generate text +generated_ids = model.generate( + **inputs, + max_new_tokens=100, +) +output = tokenizer.decode(generated_ids[0], skip_special_tokens=True) +print(output) +``` + +## Deployment + +For deployment, you can use `vllm` or `sglang` to create an OpenAI-compatible API endpoint: + +**vLLM:** +```shell +vllm serve McGill-NLP/AfriqueLlama-8B +``` + +**SGLang:** +```shell +python -m sglang.launch_server --model-path McGill-NLP/AfriqueLlama-8B +``` + +## Training Details + +### Hyperparameters + +- **Learning Rate**: 5e-5 (with warmup and cosine decay) +- **Context Length**: 16,384 tokens +- **Optimizer**: AdamW +- **Precision**: BF16 mixed precision + +### Infrastructure + +Training was conducted using the LLaMA-Factory framework on up to 64 NVIDIA H100 GPUs with: +- DeepSpeed ZeRO-1/ZeRO-2 +- Flash Attention 3 +- Sequence packing +- Liger Kernel optimizations + +## Evaluation + +All AfriqueLLM models are evaluated on multiple multilingual benchmarks: + +| Model | AfriMGSM | AfriMMLU | AfriXNLI | Belebele | FLORES | INJONG | SIB-200 | Overall | Δ | +|-------|----------|----------|----------|----------|--------|--------|---------|---------|---| +| [Gemma3-4B](https://huggingface.co/google/gemma-3-4b-pt) | 10.24 | 33.89 | 37.76 | 45.79 | 35.36 | 55.52 | 63.59 | 40.31 | | +| [AfriqueGemma-4B](https://huggingface.co/McGill-NLP/AfriqueGemma-4B) | 14.86 | 36.73 | 39.62 | 50.52 | 54.95 | 69.28 | 69.21 | 47.88 | +7.6 (18.8%) | +| [Gemma3-12B](https://huggingface.co/google/gemma-3-12b-pt) | 25.21 | 48.76 | 44.01 | 68.84 | 44.09 | 73.53 | 79.17 | 54.80 | | +| [AfriqueGemma-12B](https://huggingface.co/McGill-NLP/AfriqueGemma-12B) | 32.14 | 49.47 | 44.60 | 68.65 | 65.04 | 76.79 | 75.08 | 58.82 | +4.0 (7.3%) | +| [Qwen3-4B](https://huggingface.co/Qwen/Qwen3-4B-Base) | 8.26 | 33.84 | 37.12 | 41.50 | 20.16 | 21.69 | 57.88 | 31.49 | | +| [AfriqueQwen-4B](https://huggingface.co/McGill-NLP/AfriqueQwen-4B) | 33.09 | 43.04 | 44.88 | 63.62 | 59.82 | 65.34 | 74.77 | 54.94 | +23.4 (74.4%) | +| [Qwen3.5-4B](https://huggingface.co/Qwen/Qwen3.5-4B-Base) | 20.79 | 38.63 | 40.36 | 55.82 | 32.06 | 59.43 | 74.96 | 46.01 | | +| [AfriqueQwen3.5-4B](https://huggingface.co/McGill-NLP/AfriqueQwen3.5-4B) | 30.47 | 43.66 | 41.05 | 66.01 | 63.55 | 75.46 | 79.66 | 57.12 | +11.1 (24.2%) | +| [AfriqueQwen3.5-4B-ExtendedCM](https://huggingface.co/McGill-NLP/AfriqueQwen3.5-4B-ExtendedCM) | 34.17 | 45.26 | 41.94 | 66.45 | 63.51 | 75.97 | 80.52 | 58.26 | +1.1 (2.0%) | +| [Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B-Base) | 11.22 | 36.56 | 38.24 | 44.63 | 21.13 | 29.47 | 53.06 | 33.47 | | +| [AfriqueQwen-8B](https://huggingface.co/McGill-NLP/AfriqueQwen-8B) | 39.68 | 46.91 | 45.99 | 68.46 | 62.18 | 73.36 | 77.00 | 59.08 | +25.6 (76.5%) | +| [Qwen3-14B](https://huggingface.co/Qwen/Qwen3-14B-Base) | 16.60 | 39.66 | 43.22 | 50.74 | 23.75 | 41.80 | 66.29 | 40.29 | | +| **[AfriqueQwen-14B](https://huggingface.co/McGill-NLP/AfriqueQwen-14B)** | **45.01** | **52.22** | **49.01** | **74.63** | **63.77** | **77.80** | **82.63** | **63.58** | **+23.3 (57.8%)** | +| [Llama3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B) | 8.14 | 32.27 | 37.90 | 40.95 | 26.69 | 41.37 | 59.99 | 35.33 | | +| [AfriqueLlama-8B](https://huggingface.co/McGill-NLP/AfriqueLlama-8B) | 17.51 | 36.57 | 37.39 | 50.51 | 63.60 | 71.17 | 69.14 | 49.41 | +14.1 (39.9%) | +| [Lugha-Llama-8B-wura](https://huggingface.co/Lugha/Meta-Llama-3.1-8B-wura) | 9.46 | 37.00 | 39.24 | 47.86 | 49.90 | 62.30 | 75.81 | 45.94 | | +| [Gemma3-27B](https://huggingface.co/google/gemma-3-27b-pt) | 35.37 | 55.47 | 46.85 | 74.81 | 48.41 | 79.70 | 84.34 | 60.71 | | + +## Model Variants + +- [AfriqueQwen-14B](https://huggingface.co/McGill-NLP/AfriqueQwen-14B) - Qwen-based 14B model (flagship) +- [AfriqueQwen-8B](https://huggingface.co/McGill-NLP/AfriqueQwen-8B) - Qwen-based 8B model +- [AfriqueQwen-4B](https://huggingface.co/McGill-NLP/AfriqueQwen-4B) - Qwen-based 4B model +- [AfriqueQwen3.5-4B](https://huggingface.co/McGill-NLP/AfriqueQwen3.5-4B) - Qwen 3.5-based 4B model +- [AfriqueQwen3.5-4B-ExtendedCM](https://huggingface.co/McGill-NLP/AfriqueQwen3.5-4B-ExtendedCM) - Qwen 3.5-based 4B model with extended continued pre-training +- [AfriqueGemma-4B](https://huggingface.co/McGill-NLP/AfriqueGemma-4B) - Gemma-based 4B model +- [AfriqueGemma-12B](https://huggingface.co/McGill-NLP/AfriqueGemma-12B) - Gemma-based 12B model + +## Citation + +If you find our work helpful, please cite: + +```bibtex +@misc{yu2026afriquellmdatamixingmodel, + title={AfriqueLLM: How Data Mixing and Model Architecture Impact Continued Pre-training for African Languages}, + author={Hao Yu and Tianyi Xu and Michael A. Hedderich and Wassim Hamidouche and Syed Waqas Zamir and David Ifeoluwa Adelani}, + year={2026}, + eprint={2601.06395}, + archivePrefix={arXiv}, + primaryClass={cs.CL}, + url={https://arxiv.org/abs/2601.06395}, +} +``` + +## License + +This model is released under the [CC BY 4.0 License](https://creativecommons.org/licenses/by/4.0/). Please review the license terms before use. + +## Acknowledgments + +We thank the creators of the base models, datasets and compute resources that made this work possible, including Mila, Compute Canada, Microsoft, the FineWeb team, WURA, MADLAD-400 and etc.. diff --git a/chat_template.jinja b/chat_template.jinja new file mode 100644 index 0000000..9dd8030 --- /dev/null +++ b/chat_template.jinja @@ -0,0 +1 @@ +{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% endif %}{% if system_message is defined %}{{ system_message }}{% endif %}{% for message in loop_messages %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ content }}{% elif message['role'] == 'assistant' %}{{ content }}{% endif %}{% endfor %} \ No newline at end of file diff --git a/config.json b/config.json new file mode 100644 index 0000000..0321361 --- /dev/null +++ b/config.json 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