mirror of
https://github.com/oobabooga/text-generation-webui.git
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3e7feb699c
* many openai updates * total reorg & cleanup. * fixups * missing import os for images * +moderations, custom_stopping_strings, more fixes * fix bugs in completion streaming * moderation fix (flagged) * updated moderation categories --------- Co-authored-by: Matthew Ashton <mashton-gitlab@zhero.org>
65 lines
1.9 KiB
Python
65 lines
1.9 KiB
Python
import copy
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# Slightly different defaults for OpenAI's API
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# Data type is important, Ex. use 0.0 for a float 0
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default_req_params = {
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'max_new_tokens': 16, # 'Inf' for chat
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'temperature': 1.0,
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'top_p': 1.0,
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'top_k': 1, # choose 20 for chat in absence of another default
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'repetition_penalty': 1.18,
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'repetition_penalty_range': 0,
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'encoder_repetition_penalty': 1.0,
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'suffix': None,
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'stream': False,
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'echo': False,
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'seed': -1,
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# 'n' : default(body, 'n', 1), # 'n' doesn't have a direct map
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'truncation_length': 2048, # first use shared.settings value
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'add_bos_token': True,
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'do_sample': True,
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'typical_p': 1.0,
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'epsilon_cutoff': 0.0, # In units of 1e-4
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'eta_cutoff': 0.0, # In units of 1e-4
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'tfs': 1.0,
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'top_a': 0.0,
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'min_length': 0,
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'no_repeat_ngram_size': 0,
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'num_beams': 1,
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'penalty_alpha': 0.0,
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'length_penalty': 1.0,
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'early_stopping': False,
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'mirostat_mode': 0,
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'mirostat_tau': 5.0,
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'mirostat_eta': 0.1,
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'ban_eos_token': False,
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'skip_special_tokens': True,
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'custom_stopping_strings': '',
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# 'logits_processor' - conditionally passed
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# 'stopping_strings' - temporarily used
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# 'logprobs' - temporarily used
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# 'requested_model' - temporarily used
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}
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def get_default_req_params():
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return copy.deepcopy(default_req_params)
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# little helper to get defaults if arg is present but None and should be the same type as default.
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def default(dic, key, default):
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val = dic.get(key, default)
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if type(val) != type(default):
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# maybe it's just something like 1 instead of 1.0
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try:
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v = type(default)(val)
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if type(val)(v) == val: # if it's the same value passed in, it's ok.
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return v
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except:
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pass
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val = default
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return val
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def clamp(value, minvalue, maxvalue):
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return max(minvalue, min(value, maxvalue))
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