-
Notifications
You must be signed in to change notification settings - Fork 27
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
- Loading branch information
Showing
2 changed files
with
51 additions
and
29 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,37 +1,43 @@ | ||
| int32 n_prev 64 # number of previous tokens to remember | ||
| int32 n_probs 1 # if greater than 0, output the probabilities of top n_probs tokens | ||
| int32 min_keep 0 # 0 = disabled, otherwise samplers should return at least min_keep tokens | ||
| int32 n_prev 64 # number of previous tokens to remember | ||
| int32 n_probs 1 # if greater than 0, output the probabilities of top n_probs tokens | ||
| int32 min_keep 0 # 0 = disabled, otherwise samplers should return at least min_keep tokens | ||
|
|
||
| bool ignore_eos false # ignore end of stream token and continue generating (implies --logit-bias 2-inf) | ||
| LogitBiasArray logit_bias # logit bias for specific tokens | ||
| bool ignore_eos false # ignore end of stream token and continue generating (implies --logit-bias 2-inf) | ||
| LogitBiasArray logit_bias # logit bias for specific tokens | ||
|
|
||
| float32 temp 0.80 # temperature | ||
| float32 dynatemp_range 0.0 # 0.0 = disabled | ||
| float32 dynatemp_exponent 1.0 # controls how entropy maps to temperature in dynamic temperature sampler | ||
| float32 temp 0.80 # temperature | ||
| float32 dynatemp_range 0.0 # 0.0 = disabled | ||
| float32 dynatemp_exponent 1.0 # controls how entropy maps to temperature in dynamic temperature sampler | ||
|
|
||
| int32 top_k 40 # top-k sampling (0.0 = disabled) | ||
| float32 top_p 0.95 # top-p sampling (1.0 = disabled) | ||
| float32 xtc_probability 0.00 # xtc sampling (0.0 = disable) | ||
| float32 xtc_threshold 0.10 # xtc sampling threshold (> 0.5 disables XTC) | ||
| float32 min_p 0.05 # min-p sampling (0.0 = disabled) | ||
| float32 tfs_z 1.00 # tail free sampling, parameter z (1.0 = disabled) | ||
| float32 typical_p 1.00 # locally typical sampling, parameter p (1.0 = disabled) | ||
| int32 top_k 40 # top-k sampling (0.0 = disabled) | ||
| float32 top_p 0.95 # top-p sampling (1.0 = disabled) | ||
| float32 min_p 0.05 # min-p sampling (0.0 = disabled) | ||
| float32 xtc_probability 0.00 # xtc sampling (0.0 = disable) | ||
| float32 xtc_threshold 0.10 # xtc sampling threshold (> 0.5 disables XTC) | ||
| float32 tfs_z 1.00 # tail free sampling, parameter z (1.0 = disabled) | ||
| float32 typical_p 1.00 # locally typical sampling, parameter p (1.0 = disabled) | ||
|
|
||
| int32 penalty_last_n 64 # last n tokens consider for penalize (0 = disable penalty, -1 = context size) | ||
| float32 penalty_repeat 1.00 # penalize repeat sequence of tokens (1.0 = disabled) | ||
| float32 penalty_freq 0.00 # repeat alpha frequency penalty (0.0 = disable) | ||
| float32 penalty_present 0.00 # repeat alpha presence penalty (0.0 = disabled) | ||
| int32 penalty_last_n 64 # last n tokens consider for penalize (0 = disable penalty, -1 = context size) | ||
| float32 penalty_repeat 1.00 # penalize repeat sequence of tokens (1.0 = disabled) | ||
| float32 penalty_freq 0.00 # repeat alpha frequency penalty (0.0 = disable) | ||
| float32 penalty_present 0.00 # repeat alpha presence penalty (0.0 = disabled) | ||
|
|
||
| int32 mirostat 0 # Mirostart sampling (0 = disabled, 1 = mirostat, 2 = mirostat 2.0) | ||
| float32 mirostat_eta 0.10 # Mirostat learning rate, parameter eta | ||
| float32 mirostat_tau 5.0 # Mirostat target entropy, parameter tau | ||
| float32 dry_multiplier 0.0 # DRY repetition penalty for tokens extending repetition (0.0 = disabled) | ||
| float32 dry_base 1.75 # multiplier * base ^ (length of sequence before token - allowed length) (0.0 = disabled) | ||
| int32 dry_allowed_length 2 # tokens extending repetitions beyond this receive penalty | ||
| int32 dry_penalty_last_n -1 # how many tokens to scan for repetitions (0 = disable penalty, -1 = context size) | ||
| string[] dry_sequence_breakers ["\\n", ":", "\\\"", "*"] # default sequence breakers for DRY | ||
|
|
||
| bool penalize_nl false # consider newlines as a repeatable token | ||
| int32 mirostat 0 # Mirostart sampling (0 = disabled, 1 = mirostat, 2 = mirostat 2.0) | ||
| float32 mirostat_eta 0.10 # Mirostat learning rate, parameter eta | ||
| float32 mirostat_tau 5.0 # Mirostat target entropy, parameter tau | ||
|
|
||
| string samplers_sequence "kfypmxt" # TOP_K, TFS_Z, TYPICAL_P, TOP_P, MIN_P, XTC, TEMP | ||
| bool penalize_nl false # consider newlines as a repeatable token | ||
|
|
||
| string grammar "" # optional BNF-like grammar to constrain sampling | ||
| string grammar_schema "" # grammar schema that defines a JSON BNF grammar | ||
| string samplers_sequence "dkfypmxt" # TOP_K, TFS_Z, TYPICAL_P, TOP_P, MIN_P, XTC, TEMP | ||
|
|
||
| int32[] penalty_prompt_tokens # list of tokens to penalize | ||
| bool use_penalty_prompt_tokens false # whether to penalize tokens | ||
| string grammar "" # optional BNF-like grammar to constrain sampling | ||
| string grammar_schema "" # grammar schema that defines a JSON BNF grammar | ||
|
|
||
| int32[] penalty_prompt_tokens # list of tokens to penalize | ||
| bool use_penalty_prompt_tokens false # whether to penalize tokens |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters