StudentOne/Nifty50GPT-Final
StudentOne/Nifty50GPT-Final is a 1.1 billion parameter TinyLLaMA-based transformer model developed by Shubham Sood at Student One, specifically fine-tuned for generating SQL queries on structured Indian stock market data. It includes a bundled DuckDB database with over 10 years of historical data for NIFTY stocks and various indices, enabling offline financial analysis without external APIs or cloud dependencies. This model excels at translating natural language financial queries into executable SQL, supporting fundamental metric lookups, year-over-year growth, CAGR, OHLCV data, rolling metrics, and NIFTY-wide aggregates.
Popular Sampler Settings
Most commonly used values from Featherless users
temperature
This setting influences the sampling randomness. Lower values make the model more deterministic; higher values introduce randomness. Zero is greedy sampling.
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top_p
This setting controls the cumulative probability of considered top tokens. Must be in (0, 1]. Set to 1 to consider all tokens.
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top_k
This limits the number of top tokens to consider. Set to -1 to consider all tokens.
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frequency_penalty
This setting penalizes new tokens based on their frequency in the generated text. Values > 0 encourage new tokens; < 0 encourages repetition.
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presence_penalty
This setting penalizes new tokens based on their presence in the generated text so far. Values > 0 encourage new tokens; < 0 encourages repetition.
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repetition_penalty
This setting penalizes new tokens based on their appearance in the prompt and generated text. Values > 1 encourage new tokens; < 1 encourages repetition.
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min_p
This setting representing the minimum probability for a token to be considered relative to the most likely token. Must be in [0, 1]. Set to 0 to disable.
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