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Hathor_Tahsin-L3-8B-v0.85Nitral AI
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8B Params FP8 Inference Available

Nitral-AI/Hathor_Tahsin-L3-8B-v0.85 is an 8 billion parameter language model based on Llama 3 8B Instruct, fine-tuned for enhanced creativity, intelligence, and robust performance. It has been trained over three epochs on a diverse dataset including private roleplay, STEM instructions/dialogues, Opus instructions, and a mixture of novel data. This model excels in roleplaying and instruction-following tasks, offering a context length of 8192 tokens.

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Parameters:8BContext length:8kArchitecture:TransformerPrecision:FP8Quantized variants:AvailableLast updated:July 2024
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Nitral-AI/Hathor_Tahsin-L3-8B-v0.85
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.

1.25

top_p

This setting controls the cumulative probability of considered top tokens. Must be in (0, 1]. Set to 1 to consider all tokens.

1

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.

–

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.

–

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.

1.1

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.

0.05