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--- |
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license: apache-2.0 |
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datasets: |
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- anithasoma/refined_en_te |
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language: |
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- en |
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- te |
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metrics: |
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- bleu |
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- sacrebleu |
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base_model: |
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- facebook/nllb-200-distilled-600M |
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pipeline_tag: translation |
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library_name: transformers |
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tags: |
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- text-generation |
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- translation |
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- fine-tuned-model |
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- colloquial-language |
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- telugu |
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- machine-translation |
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--- |
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# NLLB-200 Fine-Tuned for Colloquial Telugu |
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## Model Description |
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This model is a fine-tuned version of the [NLLB-200 (Distilled 600M)](https://huggingface.co/facebook/nllb-200-distilled-600M) designed for translating English sentences into colloquial Telugu. It has been optimized to better capture informal and conversational nuances. |
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## Model Details |
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- **Model Name:** anithasoma/nllb-finetuned-telugu |
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- **Base Model:** facebook/nllb-200-distilled-600M |
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- **Fine-Tuned By:** [anithasoma](https://huggingface.co/anithasoma) |
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- **Languages:** English → Telugu (colloquial) |
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- **Framework:** Transformers (🤗 Hugging Face) |
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## 🚀 Run the Model on Google Colab |
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[](https://colab.research.google.com/drive/1CiuywF2xzdzFH7jvQ7UIrBo4tI9FI9Nf?usp=sharing) |
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Click the badge above to launch the model in Google Colab! |
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## Training Details |
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- **Dataset:** anithasoma/refined_en_te |
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- **Training Environment:** Google Colab with NVIDIA GPU. |
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- **Fine-Tuning Method:** LoRA + PEFT (Parameter Efficient Fine-Tuning) |
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- **Epochs:** Adjusted based on validation loss. |
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- **Metrics:** BLEU Score, SacreBLEU Score Perplexity, Human Evaluation. |
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## Evaluation Metrics |
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The model was evaluated using the BLEU and SacreBLEU metrics: |
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- **BLEU Score:** 43.12 |
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- **SacreBLEU Score:** 43.12 |
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## How to Use |
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You can use this model in Python with the `transformers` library: |
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```python |
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM |
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tokenizer = AutoTokenizer.from_pretrained("anithasoma/nllb-finetuned-telugu") |
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model = AutoModelForSeq2SeqLM.from_pretrained("anithasoma/nllb-finetuned-telugu") |
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def translate(text): |
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inputs = tokenizer(text, return_tensors="pt") |
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outputs = model.generate(**inputs) |
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return tokenizer.decode(outputs[0], skip_special_tokens=True) |
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print(translate("Hello, how are you?")) |
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``` |
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## Model Card |
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### Intended Use |
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This model is intended for generating colloquial Telugu translations from English text, improving conversational AI, and enhancing informal communication applications. |
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### Limitations |
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- May not perform well on formal or domain-specific text. |
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- Can sometimes produce literal rather than context-aware translations. |
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### License |
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This model is licensed under the [Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0). |
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## Contributors |
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Developed by **[anithasoma](https://huggingface.co/anithasoma)** as part of the SAWiT AI Hackathon. |
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--- |
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*For feedback or collaboration, reach out via Hugging Face!* 🚀 |
