| My Colloquial Telugu Model | |
| Overview | |
| This model is fine-tuned on colloquial Telugu text to enhance natural language understanding and generation in informal Telugu conversations. It can be used for chatbots, sentiment analysis, text classification, and other NLP tasks. | |
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| Model Details | |
| Model Name: My Colloquial Telugu Model | |
| Base Model: bert-base-multilingual-cased | |
| Training Data: Telugu colloquial dataset containing informal conversations | |
| Fine-tuning Details: | |
| Epochs: 3 | |
| Batch Size: 16 | |
| Optimizer: AdamW | |
| Language: Telugu | |
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| Usage | |
| This model can be used for text generation, classification, and translation. | |
| Using the Model in Python | |
| To use this model in Python, install the required libraries: | |
| pip install transformers torch | |
| Then, load the model: | |
| from transformers import AutoModel, AutoTokenizer | |
| model_name = "your-hf-username/my_colloquial_telugu_model" | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| model = AutoModel.from_pretrained(model_name) | |
| text = "ఇవాళ వాతావరణం ఎలా ఉంది?" | |
| inputs = tokenizer(text, return_tensors="pt") | |
| outputs = model(**inputs) | |
| print(outputs) | |
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| Performance | |
| Accuracy/F1 Score: TBD (To Be Determined) | |
| Limitations: | |
| May struggle with highly formal or technical Telugu text. | |
| Performance depends on dataset quality and coverage. | |
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| License | |
| This model is released under the Apache 2.0 license. |