| language: | |
| - en | |
| license: mit | |
| tags: | |
| - finance | |
| pipeline_tag: text-generation | |
| widget: | |
| - example_title: Easy | |
| text: '<|im_start|>user | |
| How do call options benefit the buyer?<|im_end|> | |
| <|im_start|>assistant | |
| ' | |
| - example_title: Medium | |
| text: '<|im_start|>user | |
| Why might a trader choose to quickly exit a losing position, even if they still | |
| believe in the original trade idea?<|im_end|> | |
| <|im_start|>assistant | |
| ' | |
| - example_title: Hard | |
| text: '<|im_start|>user | |
| In the context of Harry Markowitz''s Portfolio Selection theory, what does an | |
| ''efficient'' portfolio refer to?<|im_end|> | |
| <|im_start|>assistant | |
| ' | |
| inference: | |
| parameters: | |
| temperature: 0.2 | |
| min_new_tokens: 20 | |
| max_new_tokens: 250 | |
| # AlphaBlind Tiny v0.001 | |
| Our Proof-of-Concept (POC) for the LLM-ADE framework (https://arxiv.org/abs/2404.13028). A very early, initial version of TinyLlama processing and ingesting llm-ade-fin_data-subset-earnings-10k and other financial data with the LLM-ADE framework. | |
| Note: This model has not been thoroughly tested, and is very small - it can run on a Macbook Pro. Please do not use this version of the model as is. |