Update README.md

README.md

@@ -1,18 +1,15 @@
-<pre><code><span style="color:#03A9F4">from</span> transformers <span style="color:#03A9F4">import</span> AutoConfig, T5Tokenizer, 
-generator = pipeline(<span style="color:#FF9800">'text-generation'</span>,
-                     model=<span style="color:#FF9800">'huggingtweets/fidelity'</span>)
-generator(<span style="color:#FF9800">"My dream is"</span>, num_return_sequences=<span style="color:#8BC34A">5</span>)</code></pre>
-
+<pre><code><span style="color:#03A9F4">from</span> transformers <span style="color:#03A9F4">import</span> AutoConfig, T5Tokenizer
 <pre><code><span style="color:#03A9F4">from</span> fid <span style="color:#03A9F4">import</span> FiDT5
 
+tokenizer = T5Tokenizer.from_pretrained(<span style="color:#FF9800">"t5-base"</span>)
+
 question = <span style="color:#FF9800">"question:"</span>
 title = <span style="color:#FF9800">"title:"</span>
 context = <span style="color:#FF9800">"context:"</span>
-tokenizer.add_tokens([question, title, context], special_tokens=True)
-tokenizer._question = question
-tokenizer._title = title
-tokenizer._context = context
-config = AutoConfig.from_pretrained("t5-base")
-
-tokenizer = T5Tokenizer.from_pretrained("t5-base")
+tokenizer.add_tokens([question, title, context], special_tokens=<span style="color:#8BC34A">True</span>)
+config = AutoConfig.from_pretrained(<span style="color:#FF9800">"t5-base"</span>)
+model = FiDT5.from_pretrained(
+    <span style="color:#FF9800">"xfact/FiD-NQ"</span>,
+    config=<span style="color:#8BC34A">config</span>
+)
 ```