Create README.md

README.md

@@ -0,0 +1,44 @@
+---
+language: 
+- en
+thumbnail:
+widget:
+ - text: "topic climate source"
+---
+
+# GPT2-medium-topic-news
+
+## Model description
+
+GPT2-medium fine tuned on a small news corpus conditioned on a topic, source, title
+
+## Intended uses & limitations
+
+#### How to use
+
+To generate a news article text conditioned on a topic, source, title or some subsets, prompt model with: 
+```python
+f"topic {topic} source"
+f"topic {topic} source {source} title"
+f"topic {topic} source {source} title {title} body"
+```
+
+Try the following tags for `topic: climate, weather, vaccination`.
+
+Zero shot generation works pretty well as long as `topic` is a single word and not too specific.
+
+```python
+device = "cuda:0"
+tokenizer = AutoTokenizer.from_pretrained("ktrapeznikov/gpt2-medium-topic-small-set")
+model = AutoModelWithLMHead.from_pretrained("ktrapeznikov/gpt2-medium-topic-small-set")
+model.to(device)
+topic = "climate"
+prompt = tokenizer(f"topic {topics} source straitstimes title", return_tensors="pt")
+out = model.generate(prompt["input_ids"].to(device), do_sample=True,max_length=500, early_stopping=True, top_p=.9)
+print(tokenizer.decode(out[0].cpu(), skip_special_tokens=True))
+```
+
+## Training data
+
+
+## Training procedure