Tarek07/Primogenitor-V2.1-LLaMa-70B

Primogenitor-V2.1-LLaMa-70B is a 70 billion parameter language model created by Tarek07, merged using the Linear DELLA method with nbeerbower/Llama-3.1-Nemotron-lorablated-70B as its base. This model integrates components from six distinct LLaMa-based models, including Sao10K/L3.1-70B-Hanami-x1 and LatitudeGames/Wayfarer-Large-70B-Llama-3.3, to enhance its overall capabilities. With a 32768 token context length, it is designed for general-purpose language tasks, leveraging the strengths of its diverse merged constituents.

Warm
Public
70B
FP8
32768
License: llama3.3
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.
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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.
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.