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improve parameters controllable range

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This commit is contained in:
josc146 2024-03-02 16:52:53 +08:00
parent d91c3c004d
commit 53a5574080
5 changed files with 9 additions and 9 deletions
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2
backend-python/utils/rwkv.py
View File

@ -667,7 +667,7 @@ def RWKV(model: str, strategy: str, tokenizer: Union[str, None]) -> AbstractRWKV
class ModelConfigBody(BaseModel):
max_tokens: int = Field(default=None, gt=0, le=102400)
temperature: float = Field(default=None, ge=0, le=2)
temperature: float = Field(default=None, ge=0, le=3)
top_p: float = Field(default=None, ge=0, le=1)
presence_penalty: float = Field(default=None, ge=-2, le=2)
frequency_penalty: float = Field(default=None, ge=-2, le=2)

4
frontend/src/pages/Chat.tsx
View File

@ -247,7 +247,7 @@ const SidePanel: FC = observer(() => {
<Labeled flex breakline label={t('Temperature')}
desc={t('Sampling temperature, it\'s like giving alcohol to a model, the higher the stronger the randomness and creativity, while the lower, the more focused and deterministic it will be.')}
content={
<ValuedSlider value={params.temperature} min={0} max={2} step={0.1}
<ValuedSlider value={params.temperature} min={0} max={3} step={0.1}
input
onChange={(e, data) => {
commonStore.setChatParams({
@ -258,7 +258,7 @@ const SidePanel: FC = observer(() => {
<Labeled flex breakline label={t('Top_P')}
desc={t('Just like feeding sedatives to the model. Consider the results of the top n% probability mass, 0.1 considers the top 10%, with higher quality but more conservative, 1 considers all results, with lower quality but more diverse.')}
content={
<ValuedSlider value={params.topP} min={0} max={1} step={0.1} input
<ValuedSlider value={params.topP} min={0} max={1} step={0.05} input
onChange={(e, data) => {
commonStore.setChatParams({
topP: data.value

4
frontend/src/pages/Completion.tsx
View File

@ -188,7 +188,7 @@ const CompletionPanel: FC = observer(() => {
<Labeled flex breakline label={t('Temperature')}
desc={t('Sampling temperature, it\'s like giving alcohol to a model, the higher the stronger the randomness and creativity, while the lower, the more focused and deterministic it will be.')}
content={
<ValuedSlider value={params.temperature} min={0} max={2} step={0.1}
<ValuedSlider value={params.temperature} min={0} max={3} step={0.1}
input
onChange={(e, data) => {
setParams({
@ -199,7 +199,7 @@ const CompletionPanel: FC = observer(() => {
<Labeled flex breakline label={t('Top_P')}
desc={t('Just like feeding sedatives to the model. Consider the results of the top n% probability mass, 0.1 considers the top 10%, with higher quality but more conservative, 1 considers all results, with lower quality but more diverse.')}
content={
<ValuedSlider value={params.topP} min={0} max={1} step={0.1} input
<ValuedSlider value={params.topP} min={0} max={1} step={0.05} input
onChange={(e, data) => {
setParams({
topP: data.value

4
frontend/src/pages/Composition.tsx
View File

@ -275,7 +275,7 @@ const CompositionPanel: FC = observer(() => {
<Labeled flex breakline label={t('Temperature')}
desc={t('Sampling temperature, it\'s like giving alcohol to a model, the higher the stronger the randomness and creativity, while the lower, the more focused and deterministic it will be.')}
content={
<ValuedSlider value={params.temperature} min={0} max={2} step={0.1}
<ValuedSlider value={params.temperature} min={0} max={3} step={0.1}
input
onChange={(e, data) => {
setParams({
@ -286,7 +286,7 @@ const CompositionPanel: FC = observer(() => {
<Labeled flex breakline label={t('Top_P')}
desc={t('Just like feeding sedatives to the model. Consider the results of the top n% probability mass, 0.1 considers the top 10%, with higher quality but more conservative, 1 considers all results, with lower quality but more diverse.')}
content={
<ValuedSlider value={params.topP} min={0} max={1} step={0.1} input
<ValuedSlider value={params.topP} min={0} max={1} step={0.05} input
onChange={(e, data) => {
setParams({
topP: data.value

4
frontend/src/pages/Configs.tsx
View File

@ -176,7 +176,7 @@ const Configs: FC = observer(() => {
<Labeled label={t('Temperature') + ' *'}
desc={t('Sampling temperature, it\'s like giving alcohol to a model, the higher the stronger the randomness and creativity, while the lower, the more focused and deterministic it will be.')}
content={
<ValuedSlider value={selectedConfig.apiParameters.temperature} min={0} max={2} step={0.1}
<ValuedSlider value={selectedConfig.apiParameters.temperature} min={0} max={3} step={0.1}
input
onChange={(e, data) => {
setSelectedConfigApiParams({
@ -187,7 +187,7 @@ const Configs: FC = observer(() => {
<Labeled label={t('Top_P') + ' *'}
desc={t('Just like feeding sedatives to the model. Consider the results of the top n% probability mass, 0.1 considers the top 10%, with higher quality but more conservative, 1 considers all results, with lower quality but more diverse.')}
content={
<ValuedSlider value={selectedConfig.apiParameters.topP} min={0} max={1} step={0.1} input
<ValuedSlider value={selectedConfig.apiParameters.topP} min={0} max={1} step={0.05} input
onChange={(e, data) => {
setSelectedConfigApiParams({
topP: data.value