WDKT/Xiangxin-2XL-Chat-1048k-Chinese-Llama3-70B
Xiangxin-2XL-Chat-1048k is a 70 billion parameter Chat model developed by Xiangxin AI, based on Meta Llama-3-70B-Instruct and Gradient AI's expanded context work. It features a context length of up to 1 million words and is fine-tuned with a proprietary Chinese value-aligned dataset using ORPO training. This model demonstrates enhanced Chinese proficiency and cultural alignment, achieving an average score of 70.22 across eight benchmarks, surpassing Gradientai-Llama-3-70B-Instruct-Gradient-1048k.
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.
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top_p
This setting controls the cumulative probability of considered top tokens. Must be in (0, 1]. Set to 1 to consider all tokens.
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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.
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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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