Create README.md

README.md

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+---
+library_name: transformers
+tags:
+- hdfs
+- log-analysis
+- failure-prediction
+license: mit
+pipeline_tag: text-classification
+widget:
+- text: "PacketResponder: error for block blk_12345 terminating"
+---
+
+# 🚀 HDFS Failure Prediction Model
+
+**Developed by:** Shashank Choudhary ([@Sha09090](https://huggingface.co/Sha09090))  
+**License:** MIT  
+
+This model detects failures in HDFS logs with **99.95% Accuracy**.  
+It was trained on a balanced dataset of ~575k log entries.
+
+## 📊 Benchmarks
+
+| Metric | Score |
+| :--- | :--- |
+| **Accuracy** | **99.95%** |
+| **Precision** | **99.99%** |
+| **Recall** | **99.96%** |
+
+## 💻 How to Use
+
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+# Load directly from Shashank's Repo
+model_name = "Sha09090/hdfs-failure-prediction"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+
+# Predict
+log = "PacketResponder: error for block blk_12345 terminating"
+inputs = tokenizer(log, return_tensors="pt")
+with torch.no_grad():
+    logits = model(**inputs).logits
+    
+print("Failure Probability:", torch.softmax(logits, dim=1)[0][1].item())
+
+@misc{hdfs-failure-prediction,
+  author = {Shashank Choudhary},
+  title = {HDFS Failure Prediction Transformer},
+  year = {2026},
+  publisher = {Hugging Face},
+  journal = {Hugging Face Repository},
+  howpublished = {\url{[https://huggingface.co/Sha09090/hdfs-failure-prediction](https://huggingface.co/Sha09090/hdfs-failure-prediction)}}
+}