gregradzio/text-to-cypher-qwen2.5-1.5B
gregradzio/text-to-cypher-qwen2.5-1.5B is a 1.5 billion parameter model based on the Qwen2.5 architecture, developed by gregradzio. It is specifically fine-tuned for converting natural language queries into Cypher graph database queries. This model excels at generating accurate Cypher statements from user prompts, particularly when provided with a graph schema. Its primary use case is facilitating natural language interaction with Neo4j-like graph databases.
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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