Lamapi/next-4b

Lamapi/next-4b is a 4.3 billion parameter multimodal Vision-Language Model (VLM) based on Gemma 3, designed for efficient text and image understanding. As Türkiye’s first open-source VLM, it excels at visual understanding, reasoning, and creative generation, with strong multilingual capabilities including Turkish support. Optimized for low-resource deployment, it supports 8-bit quantization for consumer-grade GPUs, making it suitable for accessible multimodal AI applications.

Cold
Public
Vision
4.3B
BF16
32768
License: mit
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.
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.
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.