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*This model was contributed to Hugging Face Transformers on 2025-08-22.*

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        <img alt="SDPA" src="https://img.shields.io/badge/SDPA-DE3412?style=flat&logo=pytorch&logoColor=white">
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# SeedOss

SeedOss is ByteDance Seed's 36B-parameter dense language model with native 512K context length. It features flexible thinking budget control and strong reasoning and agent capabilities, trained on 12T tokens.

The example below demonstrates how to generate text with [`Pipeline`] or the [`AutoModelForCausalLM`] class.

<hfoptions id="usage">
<hfoption id="Pipeline">

```python
from transformers import pipeline


pipe = pipeline(
    task="text-generation",
    model="ByteDance-Seed/Seed-OSS-36B-Base",
)
pipe("The most important factor in language model training is")
```

</hfoption>
<hfoption id="AutoModelForCausalLM">

```python
from transformers import AutoModelForCausalLM, AutoTokenizer


tokenizer = AutoTokenizer.from_pretrained("ByteDance-Seed/Seed-OSS-36B-Base")
model = AutoModelForCausalLM.from_pretrained(
    "ByteDance-Seed/Seed-OSS-36B-Base",
    device_map="auto",
)
input_ids = tokenizer("The most important factor in language model training is", return_tensors="pt").to(model.device)

output = model.generate(**input_ids, max_new_tokens=50)
print(tokenizer.decode(output[0], skip_special_tokens=True))
```

</hfoption>
</hfoptions>

## SeedOssConfig

[[autodoc]] SeedOssConfig

## SeedOssModel

[[autodoc]] SeedOssModel
    - forward

## SeedOssForCausalLM

[[autodoc]] SeedOssForCausalLM
    - forward

## SeedOssForSequenceClassification

[[autodoc]] SeedOssForSequenceClassification
    - forward

## SeedOssForTokenClassification

[[autodoc]] SeedOssForTokenClassification
    - forward

## SeedOssForQuestionAnswering

[[autodoc]] SeedOssForQuestionAnswering
    - forward
