Create README.md

README.md

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