Update README.md

README.md

@@ -1,3 +1,52 @@
 ---
 license: mit
+datasets:
+- DarwinAnim8or/greentext
+language:
+- en
+tags:
+- fun
+- greentext
+widget:
+- text: ">be me"
+  example_title: "be me"
+co2_eq_emissions:
+  emissions: 60
+  source: "https://mlco2.github.io/impact/#compute"
+  training_type: "fine-tuning"
+  geographical_location: "Oregon, USA"
+  hardware_used: "1 T4, Google Colab"
 ---
+
+# GPT-DMV-125m
+A finetuned version of [GPT-Neo-125M](https://huggingface.co/EleutherAI/gpt-neo-125M) on the 'greentext' dataset. (Linked above)
+A demo is available [here](#TODO)
+
+# Training Procedure
+This was trained on the 'grug' dataset, using the "HappyTransformers" library on Google Colab.
+This model was trained for 15 epochs with learning rate 1e-2.
+
+# Biases & Limitations
+This likely contains the same biases and limitations as the original GPT-Neo-125M that it is based on, and additionally heavy biases from the greentext dataset.
+It likely will generate offensive output. 
+
+# Intended Use
+This model is meant for fun, nothing else.
+
+# Sample Use
+```python
+#Import model:
+from happytransformer import HappyGeneration
+happy_gen = HappyGeneration("GPT-NEO", "DarwinAnim8or/GPT-Greentext-125m")
+
+#Set generation settings:
+from happytransformer import GENSettings
+args_top_k = GENSettings(no_repeat_ngram_size=3, do_sample=True,top_k=80, temperature=0.4, max_length=50, early_stopping=False)
+
+#Generate a response:
+result = happy_gen.generate_text(""">be me
+>""", args=args_top_k)
+
+print(result)
+print(result.text)
+```