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oobabooga 2023-11-04 11:01:15 -07:00
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docs/03 ‐ Parameters Tab.md
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@ -33,6 +33,7 @@ For more information about the parameters, the [transformers documentation](http
* **max_new_tokens**: Maximum number of tokens to generate. Don't set it higher than necessary: it is used in the truncation calculation through the formula `(prompt_length) = min(truncation_length - max_new_tokens, prompt_length)`, so your prompt will get truncated if you set it too high.
* **temperature**: Primary factor to control the randomness of outputs. 0 = deterministic (only the most likely token is used). Higher value = more randomness.
* **top_p**: If not set to 1, select tokens with probabilities adding up to less than this number. Higher value = higher range of possible random results.
* **min_p**: Tokens with probability smaller than `(min_p) * (probability of the most likely token)` are discarded. This is the same as top_a but without squaring the probability.
* **top_k**: Similar to top_p, but select instead only the top_k most likely tokens. Higher value = higher range of possible random results.
* **repetition_penalty**: Penalty factor for repeating prior tokens. 1 means no penalty, higher value = less repetition, lower value = more repetition.
* **presence_penalty**: Similar to repetition_penalty, but with an additive offset on the raw token scores instead of a multiplicative factor. It may generate better results. 0 means no penalty, higher value = less repetition, lower value = more repetition. Previously called "additive_repetition_penalty".
@ -48,7 +49,8 @@ For more information about the parameters, the [transformers documentation](http
* **penalty_alpha**: Contrastive Search is enabled by setting this to greater than zero and unchecking "do_sample". It should be used with a low value of top_k, for instance, top_k = 4.
* **mirostat_mode**: Activates the Mirostat sampling technique. It aims to control perplexity during sampling. See the [paper](https://arxiv.org/abs/2007.14966).
* **mirostat_tau**: No idea, see the paper for details. According to the Preset Arena, 8 is a good value.
* **mirostat_tau**: No idea, see the paper for details. According to the Preset Arena, 0.1 is a good value.
* **mirostat_eta**: No idea, see the paper for details. According to the Preset Arena, 0.1 is a good value.
* **temperature_last**: Makes temperature the last sampler instead of the first. With this, you can low probability tokens with a sampler like min_p and then use a high temperature to make the model creative without losing coherency.
* **do_sample**: When unchecked, sampling is entirely disabled, and greedy decoding is used instead (the most likely token is always picked).
* **Seed**: Set the Pytorch seed to this number. Note that some loaders do not use Pytorch (notably llama.cpp), and others are not deterministic (notably ExLlama v1 and v2). For these loaders, the seed has no effect.
* **encoder_repetition_penalty**: Also known as the "Hallucinations filter". Used to penalize tokens that are *not* in the prior text. Higher value = more likely to stay in context, lower value = more likely to diverge.