Skip to content

Make right sidebar more readable in "Supported Models" #17723

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
May 6, 2025
Merged

Make right sidebar more readable in "Supported Models" #17723

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
32 changes: 24 additions & 8 deletions docs/source/models/supported_models.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -239,7 +239,9 @@ print(output)

See [this page](#generative-models) for more information on how to use generative models.

#### Text Generation (`--task generate`)
#### Text Generation

Specified using `--task generate`.

:::{list-table}
:widths: 25 25 50 5 5
Expand Down Expand Up @@ -605,7 +607,9 @@ Since some model architectures support both generative and pooling tasks,
you should explicitly specify the task type to ensure that the model is used in pooling mode instead of generative mode.
:::

#### Text Embedding (`--task embed`)
#### Text Embedding

Specified using `--task embed`.

:::{list-table}
:widths: 25 25 50 5 5
Expand Down Expand Up @@ -670,7 +674,9 @@ If your model is not in the above list, we will try to automatically convert the
{func}`~vllm.model_executor.models.adapters.as_embedding_model`. By default, the embeddings
of the whole prompt are extracted from the normalized hidden state corresponding to the last token.

#### Reward Modeling (`--task reward`)
#### Reward Modeling

Specified using `--task reward`.

:::{list-table}
:widths: 25 25 50 5 5
Expand Down Expand Up @@ -711,7 +717,9 @@ For process-supervised reward models such as `peiyi9979/math-shepherd-mistral-7b
e.g.: `--override-pooler-config '{"pooling_type": "STEP", "step_tag_id": 123, "returned_token_ids": [456, 789]}'`.
:::

#### Classification (`--task classify`)
#### Classification

Specified using `--task classify`.

:::{list-table}
:widths: 25 25 50 5 5
Expand All @@ -737,7 +745,9 @@ e.g.: `--override-pooler-config '{"pooling_type": "STEP", "step_tag_id": 123, "r
If your model is not in the above list, we will try to automatically convert the model using
{func}`~vllm.model_executor.models.adapters.as_classification_model`. By default, the class probabilities are extracted from the softmaxed hidden state corresponding to the last token.

#### Sentence Pair Scoring (`--task score`)
#### Sentence Pair Scoring

Specified using `--task score`.

:::{list-table}
:widths: 25 25 50 5 5
Expand Down Expand Up @@ -824,7 +834,9 @@ vLLM currently only supports adding LoRA to the language backbone of multimodal

See [this page](#generative-models) for more information on how to use generative models.

#### Text Generation (`--task generate`)
#### Text Generation

Specified using `--task generate`.

:::{list-table}
:widths: 25 25 15 20 5 5 5
Expand Down Expand Up @@ -1200,7 +1212,9 @@ Since some model architectures support both generative and pooling tasks,
you should explicitly specify the task type to ensure that the model is used in pooling mode instead of generative mode.
:::

#### Text Embedding (`--task embed`)
#### Text Embedding

Specified using `--task embed`.

Any text generation model can be converted into an embedding model by passing `--task embed`.

Expand Down Expand Up @@ -1240,7 +1254,9 @@ The following table lists those that are tested in vLLM.
* ✅︎
:::

#### Transcription (`--task transcription`)
#### Transcription

Specified using `--task transcription`.

Speech2Text models trained specifically for Automatic Speech Recognition.

Expand Down