bitsandbytes/pr_2030/en/reference/optim/lion.md

# Lion

[Lion (Evolved Sign Momentum)](https://hf.co/papers/2302.06675) is a unique optimizer that uses the sign of the gradient to determine the update direction of the momentum. This makes Lion more memory-efficient and faster than `AdamW` which tracks and store the first and second-order moments.

## Lion[[api-class]][[bitsandbytes.optim.Lion]]

#### bitsandbytes.optim.Lion[[bitsandbytes.optim.Lion]]

```python
bitsandbytes.optim.Lion(params, lr = 0.0001, betas = (0.9, 0.99), weight_decay = 0, optim_bits = 32, args = None, min_8bit_size = 4096, is_paged = False)
```

[Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2030/bitsandbytes/optim/lion.py#L8)

#### __init__[[bitsandbytes.optim.Lion.__init__]]

```python
__init__(params, lr = 0.0001, betas = (0.9, 0.99), weight_decay = 0, optim_bits = 32, args = None, min_8bit_size = 4096, is_paged = False)
```

[Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2030/bitsandbytes/optim/lion.py#L9)

**Parameters:**

params (`torch.tensor`) : The input parameters to optimize.

lr (`float`, defaults to 1e-4) : The learning rate.

betas (`tuple(float, float)`, defaults to (0.9, 0.999)) : The beta values are the decay rates of the first and second-order moment of the optimizer.

weight_decay (`float`, defaults to 0) : The weight decay value for the optimizer.

optim_bits (`int`, defaults to 32) : The number of bits of the optimizer state.

args (`object`, defaults to `None`) : An object with additional arguments.

min_8bit_size (`int`, defaults to 4096) : The minimum number of elements of the parameter tensors for 8-bit optimization.

is_paged (`bool`, defaults to `False`) : Whether the optimizer is a paged optimizer or not.

Base Lion optimizer.

## Lion8bit[[bitsandbytes.optim.Lion8bit]]

#### bitsandbytes.optim.Lion8bit[[bitsandbytes.optim.Lion8bit]]

```python
bitsandbytes.optim.Lion8bit(params, lr = 0.0001, betas = (0.9, 0.99), weight_decay = 0, args = None, min_8bit_size = 4096, is_paged = False)
```

[Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2030/bitsandbytes/optim/lion.py#L55)

#### __init__[[bitsandbytes.optim.Lion8bit.__init__]]

```python
__init__(params, lr = 0.0001, betas = (0.9, 0.99), weight_decay = 0, args = None, min_8bit_size = 4096, is_paged = False)
```

[Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2030/bitsandbytes/optim/lion.py#L56)

**Parameters:**

params (`torch.tensor`) : The input parameters to optimize.

lr (`float`, defaults to 1e-4) : The learning rate.

betas (`tuple(float, float)`, defaults to (0.9, 0.999)) : The beta values are the decay rates of the first and second-order moment of the optimizer.

weight_decay (`float`, defaults to 0) : The weight decay value for the optimizer.

args (`object`, defaults to `None`) : An object with additional arguments.

min_8bit_size (`int`, defaults to 4096) : The minimum number of elements of the parameter tensors for 8-bit optimization.

is_paged (`bool`, defaults to `False`) : Whether the optimizer is a paged optimizer or not.

8-bit Lion optimizer.

## Lion32bit[[bitsandbytes.optim.Lion32bit]]

#### bitsandbytes.optim.Lion32bit[[bitsandbytes.optim.Lion32bit]]

```python
bitsandbytes.optim.Lion32bit(params, lr = 0.0001, betas = (0.9, 0.99), weight_decay = 0, args = None, min_8bit_size = 4096, is_paged = False)
```

[Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2030/bitsandbytes/optim/lion.py#L99)

#### __init__[[bitsandbytes.optim.Lion32bit.__init__]]

```python
__init__(params, lr = 0.0001, betas = (0.9, 0.99), weight_decay = 0, args = None, min_8bit_size = 4096, is_paged = False)
```

[Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2030/bitsandbytes/optim/lion.py#L100)

**Parameters:**

params (`torch.tensor`) : The input parameters to optimize.

lr (`float`, defaults to 1e-4) : The learning rate.

betas (`tuple(float, float)`, defaults to (0.9, 0.999)) : The beta values are the decay rates of the first and second-order moment of the optimizer.

weight_decay (`float`, defaults to 0) : The weight decay value for the optimizer.

args (`object`, defaults to `None`) : An object with additional arguments.

min_8bit_size (`int`, defaults to 4096) : The minimum number of elements of the parameter tensors for 8-bit optimization.

is_paged (`bool`, defaults to `False`) : Whether the optimizer is a paged optimizer or not.

32-bit Lion optimizer.

## PagedLion[[bitsandbytes.optim.PagedLion]]

#### bitsandbytes.optim.PagedLion[[bitsandbytes.optim.PagedLion]]

```python
bitsandbytes.optim.PagedLion(params, lr = 0.0001, betas = (0.9, 0.99), weight_decay = 0, optim_bits = 32, args = None, min_8bit_size = 4096)
```

[Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2030/bitsandbytes/optim/lion.py#L143)

#### __init__[[bitsandbytes.optim.PagedLion.__init__]]

```python
__init__(params, lr = 0.0001, betas = (0.9, 0.99), weight_decay = 0, optim_bits = 32, args = None, min_8bit_size = 4096)
```

[Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2030/bitsandbytes/optim/lion.py#L144)

**Parameters:**

params (`torch.tensor`) : The input parameters to optimize.

lr (`float`, defaults to 1e-4) : The learning rate.

betas (`tuple(float, float)`, defaults to (0.9, 0.999)) : The beta values are the decay rates of the first and second-order moment of the optimizer.

weight_decay (`float`, defaults to 0) : The weight decay value for the optimizer.

optim_bits (`int`, defaults to 32) : The number of bits of the optimizer state.

args (`object`, defaults to `None`) : An object with additional arguments.

min_8bit_size (`int`, defaults to 4096) : The minimum number of elements of the parameter tensors for 8-bit optimization.

Paged Lion optimizer.

## PagedLion8bit[[bitsandbytes.optim.PagedLion8bit]]

#### bitsandbytes.optim.PagedLion8bit[[bitsandbytes.optim.PagedLion8bit]]

```python
bitsandbytes.optim.PagedLion8bit(params, lr = 0.0001, betas = (0.9, 0.99), weight_decay = 0, args = None, min_8bit_size = 4096)
```

[Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2030/bitsandbytes/optim/lion.py#L187)

#### __init__[[bitsandbytes.optim.PagedLion8bit.__init__]]

```python
__init__(params, lr = 0.0001, betas = (0.9, 0.99), weight_decay = 0, args = None, min_8bit_size = 4096)
```

[Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2030/bitsandbytes/optim/lion.py#L188)

**Parameters:**

params (`torch.tensor`) : The input parameters to optimize.

lr (`float`, defaults to 1e-4) : The learning rate.

betas (`tuple(float, float)`, defaults to (0.9, 0.999)) : The beta values are the decay rates of the first and second-order moment of the optimizer.

weight_decay (`float`, defaults to 0) : The weight decay value for the optimizer.

args (`object`, defaults to `None`) : An object with additional arguments.

min_8bit_size (`int`, defaults to 4096) : The minimum number of elements of the parameter tensors for 8-bit optimization.

Paged 8-bit Lion optimizer.

## PagedLion32bit[[bitsandbytes.optim.PagedLion32bit]]

#### bitsandbytes.optim.PagedLion32bit[[bitsandbytes.optim.PagedLion32bit]]

```python
bitsandbytes.optim.PagedLion32bit(params, lr = 0.0001, betas = (0.9, 0.99), weight_decay = 0, args = None, min_8bit_size = 4096)
```

[Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2030/bitsandbytes/optim/lion.py#L228)

#### __init__[[bitsandbytes.optim.PagedLion32bit.__init__]]

```python
__init__(params, lr = 0.0001, betas = (0.9, 0.99), weight_decay = 0, args = None, min_8bit_size = 4096)
```

[Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2030/bitsandbytes/optim/lion.py#L229)

**Parameters:**

params (`torch.tensor`) : The input parameters to optimize.

lr (`float`, defaults to 1e-4) : The learning rate.

betas (`tuple(float, float)`, defaults to (0.9, 0.999)) : The beta values are the decay rates of the first and second-order moment of the optimizer.

weight_decay (`float`, defaults to 0) : The weight decay value for the optimizer.

args (`object`, defaults to `None`) : An object with additional arguments.

min_8bit_size (`int`, defaults to 4096) : The minimum number of elements of the parameter tensors for 8-bit optimization.

Paged 32-bit Lion optimizer.