Update README.md

README.md

@@ -1,6 +1,54 @@
 ---
 library_name: peft
+license: apache-2.0
+datasets:
+- ThatOneShortGuy/SongLyrics
+language:
+- en
+tags:
+- music
 ---
+# Musical Falcon
+
+[OpenAssistant/falcon-7b-sft-mix-2000](https://huggingface.co/OpenAssistant/falcon-7b-sft-mix-2000) model fine tuned using PEFT on
+[Song Lyrics](https://huggingface.co/datasets/ThatOneShortGuy/SongLyrics) to write lyrics to songs.
+
+## Model Details
+- **Finetuned from**: [OpenAssistant/falcon-7b-sft-mix-2000]
+- **Model Type**: Causal decoder-only transformer language model
+- **Language**: English (and limited capabilities in German, Spanish, French, Italian, Portuguese, Polish, Dutch, Romanian, Czech, Swedish);
+- **License**: Apache 2.0
+- **Contact**: Lol don't. This is just for fun.
+
+## Usage
+The basic basic format getting it in is:
+```python
+from peft import PeftModel, PeftConfig
+from transformers import AutoModelForCausalLM
+
+config = PeftConfig.from_pretrained("ThatOneShortGuy/MusicalFalcon")
+model = AutoModelForCausalLM.from_pretrained("OpenAssistant/falcon-7b-sft-mix-2000")
+model = PeftModel.from_pretrained(model, "ThatOneShortGuy/MusicalFalcon")
+```
+
+## Prompting
+Considering this comes from [OpenAssistant/falcon-7b-sft-mix-2000](https://huggingface.co/OpenAssistant/falcon-7b-sft-mix-2000), it uses the same structure.
+Two special tokens are used to mark the beginning of user and assistant turns: `<|prompter|>` and `<|assistant|>`. Each turn ends with a `<|endoftext|>` token.
+The training prompt used the structure: 
+```
+<|prompter|>Come up with the lyrics for a song from "{artist}" {"from " + year if year else ""} titled "{title}".<|endoftext|>
+<|assistant|>Sure! Here are the lyrics:
+{lyrics}
+<|endoftext|>
+```
+
+However, it still seems to work just fine using:
+```
+<|prompter|>Write me a song titled "{title}"<|endoftext|><|assistant|>
+```
+or any anything of similar nature. Feel free to add a description of the song in there too.
+
+
 ## Training procedure
 
 
@@ -17,4 +65,4 @@ The following `bitsandbytes` quantization config was used during training:
 ### Framework versions
 
 
-- PEFT 0.5.0.dev0
+- PEFT 0.5.0.dev0