Quantization made by Richard Erkhov.
-
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
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.
