Update README.md

README.md

@@ -1,3 +1,58 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+datasets:
+- squad
+- adversarial_qa
+language:
+- en
+metrics:
+- exact_match
+- f1
+base_model:
+- albert/albert-base-v2
+model: xichenn/albert-base-v2-squad-fp16
+library_name: transformers
+model-index:
+- name: xichenn/albert-base-v2-squad-fp16
+  results:
+  - task:
+      type: question-answering
+      name: Question Answering
+    dataset:
+      name: squad
+      type: squad
+      config: plain_text
+      split: validation
+    metrics:
+    - type: exact_match
+      value: 84.68
+      name: Exact Match
+      verified: true
+    - type: f1
+      value: 91.4
+      name: F1
+      verified: true
+---
+
+# albert-base-v2-squad-fp16
+
+This model is a fp16 quantized version of [albert-base-v2-squad](https://huggingface.co/xichenn/albert-base-v2-squad).
+It achieves the following results on the SQuAD 1.1 evaluation set (no model accuracy loss compared to fp32):
+- Exact Match(EM): 84.68
+- F1: 91.40
+
+## Inference API
+
+You can test the model directly using the Hugging Face Inference API:
+
+```python
+from transformers import pipeline
+
+# Load the pipeline
+qa_pipeline = pipeline("question-answering", model="xichenn/albert-base-v2-squad-fp16")
+
+# Run inference
+result = qa_pipeline(question="What is the capital of France?", context="France is a country in Europe. Its capital is Paris.")
+
+print(result)
+```