Update README.md

README.md

@@ -1,76 +1,86 @@
-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.
-
-
----
-
-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
-
-
-
----
-
-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)
-
-
----
-
-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.
-
-
-
-
----
-
-License
-
+---
+license: apache-2.0
+datasets:
+- jaksani1/TeluguDataset
+language:
+- te
+- en
+base_model:
+- google-bert/bert-base-multilingual-cased
+---
+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.
+
+
+---
+
+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
+
+
+
+---
+
+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)
+
+
+---
+
+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.
+
+
+
+
+---
+
+License
+
 This model is released under the Apache 2.0 license.