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Model: sh4lu-z/Sinhala-Qwen3-v7500
Source: Original Platform

README.md

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+---
+base_model: qwen3
+language:
+  - si
+  - en
+pipeline_tag: text-generation
+library_name: transformers
+license: apache-2.0
+datasets:
+  - your_dataset_name_here
+tags:
+  - unsloth
+  - qwen
+  - qwen3
+  - sinhala
+  - text-generation
+  - custom-finetune
+  - causal-lm
+  - nlp
+  - pytorch
+---
+
+# Sinhala Qwen 3 - Fine-Tuned Model (v7500)
+
+## Model Description
+This is a fine-tuned version of the **Qwen 3** base model, specifically trained to understand and generate the **Sinhala** language. 
+
+Originally, the base model had absolutely no understanding of Sinhala. Through custom fine-tuning using the [Unsloth](https://github.com/unslothai/unsloth) library, this model has been taught the foundational elements of the language from scratch. It is now capable of basic Sinhala comprehension and text generation, marking a significant step in low-resource language adaptation for this architecture.
+
+## Model Details
+* **Base Model:** Qwen 3 (`Qwen3ForCausalLM`)
+* **Language(s):** Sinhala (si), English (en)
+* **Fine-Tuning Library:** Unsloth (`unsloth_version: 2026.1.4`)
+* **Checkpoint/Version:** v7500 (Trained up to 7500 steps)
+* **Status:** Experimental / Early Stage
+
+## Intended Use
+This model is intended for researchers and developers working on Natural Language Processing (NLP) for the Sinhala language. It can be used as a starting point for further fine-tuning, vocabulary expansion, or basic Sinhala text generation tasks.
+
+*Note: Since the model was trained from scratch to learn a completely new language, it might still make grammatical errors or occasionally struggle with complex sentence structures. It represents a foundation that is continuously being improved.*
+
+## How to Use
+
+You can use this model directly with the `transformers` library in Python:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+
+model_id = "sh4lu-z/Sinhala-Qwen3-v7500" 
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")
+
+prompt = "ඔබට කොහොමද?"
+inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
+outputs = model.generate(**inputs, max_new_tokens=50)
+
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Training Procedure
+
+This model was trained using the Unsloth library to significantly speed up the fine-tuning process while maintaining accuracy.
+
+#### `Framework:` PyTorch / Transformers
+
+#### `Hardware:` Fine-tuned on GPU instances