inclusionAI/Ling-1T
Ling-1T is a 1 trillion total parameter, 50 billion active parameter model from inclusionAI, built on the Ling 2.0 architecture. Pre-trained on over 20 trillion reasoning-dense tokens, it supports up to 128K context length and utilizes an evolutionary chain-of-thought (Evo-CoT) process. This model excels in efficient complex reasoning, outperforming leading models on benchmarks like AIME 25, and demonstrates strong capabilities in visual aesthetics and front-end code generation.
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Hugging Face 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.
top_p
This setting controls the cumulative probability of considered top tokens. Must be in (0, 1]. Set to 1 to consider all tokens.
top_k
This limits the number of top tokens to consider. Set to -1 to consider all tokens.
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.
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.