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*This model was released on 2025-01-14 and added to Hugging Face Transformers on 2025-06-04 and contributed by [geetu040](https://github.com/geetu040) and [Shakib-IO](https://github.com/Shakib-IO).*

# MiniMax

[MiniMax-Text-01](https://huggingface.co/papers/2501.08313) is part of the MiniMax-01 series, featuring superior capabilities in processing longer contexts through lightning attention and efficient scaling. It integrates Mixture of Experts (MoE) with 32 experts and 456 billion total parameters, of which 45.9 billion are activated per token. Optimized parallel strategies and compute-communication overlap techniques enable efficient training and inference on models with hundreds of billions of parameters. MiniMax-Text-01 supports a training context length of up to 1 million tokens and can handle up to 4 million tokens during inference. The model demonstrates performance comparable to top-tier models like GPT-4o and Claude-3.5-Sonnet while offering significantly longer context windows.

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

```py
import torch
from transformers import pipeline

pipeline = pipeline(task="text-generation", model="MiniMaxAI/MiniMax-Text-01-hf", dtype="auto",)
pipeline("Plants create energy through a process known as photosynthesis.")
```

</hfoption>
<hfoption id="AutoModel">

```py
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("MiniMaxAI/MiniMax-Text-01-hf")
model = AutoModelForCausalLM.from_pretrained("MiniMaxAI/MiniMax-Text-01-hf", dtype="auto",)

inputs = tokenizer("Plants create energy through a process known as photosynthesis.", return_tensors="pt")
outputs = model.generate(**inputs, max_length=50)
print(tokenizer.decode(outputs[0]))
```

</hfoption>
</hfoptions>

## MiniMaxConfig

[[autodoc]] MiniMaxConfig

## MiniMaxModel

[[autodoc]] MiniMaxModel
    - forward

## MiniMaxForCausalLM

[[autodoc]] MiniMaxForCausalLM
    - forward

## MiniMaxForSequenceClassification

[[autodoc]] MiniMaxForSequenceClassification
    - forward

## MiniMaxForTokenClassification

[[autodoc]] MiniMaxForTokenClassification
    - forward

## MiniMaxForQuestionAnswering
[[autodoc]] MiniMaxForQuestionAnswering
    - forward
