Update README.md

README.md

@@ -1,32 +1,50 @@
 ---
 tags:
-- generated_from_trainer
-model-index:
-- name: gpt-peter-2pt7B-peter_DS-msgs_Ep-1_Bs-2
-  results: []
+- gpt-neo
+- gpt-peter
+- chatbot
+
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
 
-# gpt-peter-2pt7B-peter_DS-msgs_Ep-1_Bs-2
+# pszemraj/gpt-peter-2.7B
+
+- This model is a fine-tuned version of [EleutherAI/gpt-neo-2.7B](https://huggingface.co/EleutherAI/gpt-neo-2.7B) on about 80k WhatsApp and iMessage texts.
+- The model is too large to use the inference API. linked [here](https://colab.research.google.com/gist/pszemraj/a59b43813437b43973c8f8f9a3944565/testing-pszemraj-gpt-peter-2-7b.ipynb) is a notebook for testing in Colab.
+    - alternatively, you can message [a bot on telegram](http://t.me/GPTPeter_bot) based on this model
+    - the telegram bot code and the model training code can be found [in this repository](https://github.com/pszemraj/ai-msgbot)
+                      
 
-This model is a fine-tuned version of [pszemraj/gpt-peter-2.7B](https://huggingface.co/pszemraj/gpt-peter-2.7B) on the None dataset.
+## Usage in python 
 
-## Model description
+Install the transformers library if you don't have it:
+```
+pip install -U transformers
+```
 
-More information needed
+load the model into a `pipeline` object:
 
-## Intended uses & limitations
+```
+from transformers import pipeline
+import torch
+device = 'cuda' if torch.cuda.is_available() else 'cpu'
+my_chatbot = pipeline('text-generation', 
+                      'pszemraj/gpt-peter-2.7B',
+                      device=0 if device == 'cuda' else -1,
+                    )
+```
 
-More information needed
+generate text!
 
-## Training and evaluation data
+```
+my_chatbot('Did you ever hear the tragedy of Darth Plagueis The Wise?')
+```
 
-More information needed
+_(example above for simplicity, but adding generation parameters such as `no_repeat_ngram_size` are recommended to get better generations)_
 
 ## Training procedure
 
+
 ### Training hyperparameters
 
 The following hyperparameters were used during training: