Vikhrmodels/Vikhr-Nemo-12B-Instruct-R-21-09-24
VikhrModels' Vikhr-Nemo-12B-Instruct-R-21-09-24 is a 12 billion parameter unimodal LLM, an enhanced version of Mistral-Nemo-Instruct-2407, primarily adapted for Russian and English. It features a 32768-token context length and is optimized for reasoning, summarization, code generation, roleplay, dialogue, and high-performance RAG capabilities. The model was trained using SFT and SMPO, a custom DPO variation, and includes a unique Grounded RAG mode for document-based question answering.
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.
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.
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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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