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Model: SAWithanage/SinLlama-Llama-3-8B-Merged
Source: Original Platform

.gitattributes

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README.md

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+---
+language:
+- si
+- en
+base_model: meta-llama/Meta-Llama-3-8B
+tags:
+- llama-3
+- sinhala
+- nlp
+- text-generation
+- merged
+license: llama3
+---
+
+# SinLlama Llama-3-8B Merged
+
+This repository contains a continuous pre-trained (CPT) base model for the Sinhala language. It was created by mathematically merging the official `meta-llama/Meta-Llama-3-8B` base model with the `polyglots/SinLlama_v01` LoRA adapter. 
+
+**This model has been fully merged into standalone FP16 weights**, meaning it can be loaded directly in libraries like `transformers` or `vLLM` without needing to download or manage separate Peft adapters.
+
+## 🏆 Acknowledgments, Credits & Disclaimer
+**My contribution to this repository is strictly limited to merging the weights to provide a convenient standalone model.** 
+
+All credit for the foundational machine learning research, tokenizer vocabulary expansion, dataset curation, and continuous pre-training (CPT) belongs entirely to the **[Polyglots](https://huggingface.co/polyglots)** team and the authors of the SinLlama paper.
+
+*   **Researchers/Authors:** H. W. K. Aravinda, Rashad Sirajudeen, Samith Karunathilake, Nisansa de Silva, Surangika Ranathunga, Rishemjit Kaur
+*   **Original Adapter:** [polyglots/SinLlama_v01](https://huggingface.co/polyglots/SinLlama_v01)
+*   **Original Tokenizer:** [polyglots/Extended-Sinhala-LLaMA](https://huggingface.co/polyglots/Extended-Sinhala-LLaMA)
+*   **Paper:** *SinLlama: A Large Language Model for Sinhala*
+
+If you use this model in your research or applications, please ensure you cite their original work:
+```bibtex
+@article{aravinda2025sinllama,
+  title={SinLlama-A Large Language Model for Sinhala},
+  author={Aravinda, H W K and Sirajudeen, Rashad and Karunathilake, Samith and de Silva, Nisansa and Ranathunga, Surangika and Kaur, Rishemjit},
+  journal={arXiv preprint arXiv:2508.09115},
+  year={2025}
+}
+```
+
+## ⚙️ Model Details
+* **Base Model:** [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B)
+* **Language:** Sinhala (si), English (en)
+* **Architecture:** Llama 3 (8 Billion Parameters)
+* **Format:** Safetensors (Unquantized FP16)
+
+## ⚠️ Important Limitations (Base Model vs. Chat Model)
+**This is a Base Model, not an Instruction-Tuned (Chat) Model.** 
+Because it has not undergone Supervised Fine-Tuning (SFT), it is optimized for text completion, not interactive conversation. 
+
+If you prompt it with a question, it may attempt to complete the document by writing more questions (acting like an FAQ page). To use it effectively for Q&A, you must format your prompts strictly and use stopping criteria (like regex or EOS tokens) to prevent looping and run-on generations.
+
+### Example Prompt Format:
+```text
+Question: කෘතිම බුද්ධිය (AI) යනු කුමක්දැයි සරලව පැහැදිලි කරන්න.
+Answer: 
+```
+
+## 💻 How to Load in 4-bit (Google Colab / T4 GPU)
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
+import torch
+
+bnb_config = BitsAndBytesConfig(
+    load_in_4bit=True,
+    bnb_4bit_use_double_quant=True,
+    bnb_4bit_quant_type="nf4",
+    bnb_4bit_compute_dtype=torch.float16
+)
+
+tokenizer = AutoTokenizer.from_pretrained("SAWithanage/SinLlama-Llama-3-8B-Merged")
+model = AutoModelForCausalLM.from_pretrained(
+    "SAWithanage/SinLlama-Llama-3-8B-Merged",
+    quantization_config=bnb_config,
+    device_map="auto"
+)
+```

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "dtype": "float16",
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+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 8192,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pad_token_id": null,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_parameters": {
+    "rope_theta": 500000.0,
+    "rope_type": "default"
+  },
+  "tie_word_embeddings": false,
+  "transformers_version": "5.0.0",
+  "use_cache": true,
+  "vocab_size": 139336
+}

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+  "do_sample": true,
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+  "max_length": 4096,
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "5.0.0"
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