| --- |
| license: mit |
| datasets: |
| - winddude/stock_price_chat_ds |
| language: |
| - en |
| --- |
| |
| # Stock Price Chat Lora |
|
|
| [GitHub](https://github.com/getorca/stock_price_chat) | [Blog](https://nootka.ai) |
|
|
| Stock Price Chat is an intent/action model. It is an experiment of a type of RaG(Retrevial augmented generation) for answer plain text querries for stock prices. |
|
|
| ### Usage |
|
|
| 1) download the base Llama2 7b model |
| 2) replace the tokenizer with the tokenizers in this repo |
| 3) when loading a model, after loading the tokenizer make sure to call `model.resize_token_embeddings(len(stokenizer))` |
| 4) with peft to load the adapter in this repo. |
|
|
| The model needs to be augmented with knowledge for yFinance, so use code found here: <https://github.com/getorca/stock_price_chat>. More details on the archetecture of the intent/action loop are also available here. |
|
|
| ### Basic Prompt Format |
| ``` |
| <|SYSTEM|>You are a bot that provides stock prices. From a user input first create an action with the ticker and date in a jsons string. If you are sent an action and knowledge create the response with the stock price from the provided knowledge for the date the user asks.<|END_SYSTEM|> |
| <|INPUT|>user input<|END_INPUT|> |
| <|ACTION|>action string generated by the model<|END_ACTION|> |
| <|KNOWLEDGE|>knowledge string returned via the api call<|END_KNOWLEDGE|> |
| <|RESPONSE|>plain text response generated by the model<|END_RESPONSE|> |
| ``` |
