Create README.md

README.md

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+---
+license: cc-by-nc-4.0
+language:
+- en
+tags:
+- English
+- RoBERTa-base
+- Text Classification
+pipeline_tag: text-classification
+---
+
+# RoBERTa base Fine-Tuned for Proposal Sentence Classification
+
+## Overview
+
+- **Language**: English
+- **Model Name**: oeg/SciBERT-Repository-Proposal
+  
+## Description
+
+This model is a fine-tuned allenai/scibert_scivocab_uncased model trained to classify sentences into two classes: proposal and non-proposal sentences. The training data includes sentences proposing a software or data repository. The model is trained to recognize and classify these sentences accurately.
+
+## How to use
+
+To use this model in Python:
+
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+tokenizer = AutoTokenizer.from_pretrained("allenai/scibert_scivocab_uncased")
+model = AutoModelForSequenceClassification.from_pretrained("scibert-model")
+
+sentence = "Your input sentence here."
+inputs = tokenizer(sentence, return_tensors="pt")
+outputs = model(**inputs)
+probabilities = torch.nn.functional.softmax(outputs.logits, dim=1)