Doctor-Shotgun/TinyLlama-1.1B-32k

Doctor-Shotgun/TinyLlama-1.1B-32k is a 1.1 billion parameter language model, a 32k context fine-tune of TinyLlama-1.1B. It utilizes an increased RoPE theta (rope frequency base) to extend its context window, primarily designed for long-context speculative decoding. This model excels at maintaining performance over extended context lengths, making it suitable for applications requiring processing of large text inputs.

Warm
Public
1.1B
BF16
2048
License: apache-2.0
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.
–