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Functions2,622 in github.com/ml-explore/mlx-lm

⨍ Functions 2,622◇ Types & classes 816↳ Endpoints 9
Method__call__
(self, x)
mlx_lm/models/nemotron_h.py:408
Method__call__
( self, x, mask: Optional[mx.array] = None, cache: Optional[Any] = None, )
mlx_lm/models/nemotron_h.py:443
Method__call__
( self, inputs, cache: Optional[Any] = None, )
mlx_lm/models/nemotron_h.py:480
Method__call__
( self, inputs: mx.array, cache: Optional[Any] = None, )
mlx_lm/models/nemotron_h.py:517
Method__call__
( self, x: mx.array, mask: Optional[mx.array] = None, cache: Optional[Any] = N
mlx_lm/models/llama4_text.py:58
Method__call__
(self, x: mx.array)
mlx_lm/models/llama4_text.py:98
Method__call__
( self, x: mx.array, mask: Optional[mx.array] = None, cache: Optional[Any] = N
mlx_lm/models/llama4_text.py:117
Method__call__
( self, inputs: mx.array, cache: Optional[Any] = None, )
mlx_lm/models/llama4_text.py:141
Method__call__
( self, inputs: mx.array, cache: Optional[Any] = None, )
mlx_lm/models/llama4_text.py:169
Method__call__
( self, x: mx.array, mask: Optional[mx.array] = None, cache: Optional[Any] = N
mlx_lm/models/exaone4.py:64
Method__call__
(self, x)
mlx_lm/models/exaone4.py:105
Method__call__
( self, x: mx.array, mask: Optional[mx.array] = None, cache: Optional[Any] = N
mlx_lm/models/exaone4.py:124
Method__call__
( self, inputs: mx.array, cache=None, )
mlx_lm/models/exaone4.py:163
Method__call__
( self, inputs: mx.array, cache=None, )
mlx_lm/models/exaone4.py:196
Method__deepcopy__
(self, memo)
mlx_lm/generate.py:980
Method__del__
(self)
mlx_lm/generate.py:1561
Method__eq__
(self, other)
tests/test_server.py:84
Method__eq__
(self, other)
mlx_lm/share.py:38
Method__getattr__
(self, attr)
mlx_lm/tokenizer_utils.py:457
Method__getitem__
(self, idx: int)
mlx_lm/tuner/datasets.py:32
Method__getitem__
(self, idx: int)
mlx_lm/tuner/datasets.py:79
Method__getitem__
(self, idx: int)
mlx_lm/tuner/datasets.py:129
Method__getitem__
(self, idx: int)
mlx_lm/tuner/datasets.py:141
Method__getitem__
(self, idx: int)
mlx_lm/tuner/datasets.py:166
Method__getitem__
(self, idx)
mlx_lm/models/cache.py:621
Method__getitem__
(self, idx)
mlx_lm/models/cache.py:818
Method__init__
(self, rank, size)
tests/test_tuner_trainer.py:11
Method__init__
(self, with_draft=False)
tests/test_server.py:25
Method__init__
(self, value, is_trimmable: bool = True)
tests/test_server.py:76
Method__init__
(self, args)
tests/test_utils.py:100
Method__init__
(self, tokenizer)
mlx_lm/tokenizer_utils.py:69
Method__init__
(self, tokenizer, trim_space=True)
mlx_lm/tokenizer_utils.py:114
Method__init__
(self, tokenizer)
mlx_lm/tokenizer_utils.py:165
Method__init__
(self, *args, **kwargs)
mlx_lm/tokenizer_utils.py:482
Method__init__
( self, fname_tokenizer: Path, fname_added_tokens: Optional[Union[Path, None]] = None,
mlx_lm/gguf.py:25
Method__init__
(self, transitions={}, initial="normal")
mlx_lm/generate.py:971
Method__init__
( self, model: nn.Module, uids: List[int], caches: List[List[Any]], to
mlx_lm/generate.py:1019
Method__init__
( self, model: nn.Module, uids: List[int], inputs: mx.array, prompt_ca
mlx_lm/generate.py:1248
Method__init__
( self, model: nn.Module, *, max_tokens: int = 128, stop_tokens: Optio
mlx_lm/generate.py:1497
Method__init__
(self, tool_parser, tools, streaming=False)
mlx_lm/server.py:55
Method__init__
Load models on demand and persist them across the whole process.
mlx_lm/server.py:293
Method__init__
(self, model_provider: ModelProvider, prompt_cache: LRUPromptCache)
mlx_lm/server.py:441
Method__init__
Create static request specific metadata
mlx_lm/server.py:1060
Method__init__
( self, path_or_hf_repo: str, max_tokens: Optional[int] = None, batch_size: in
mlx_lm/evaluate.py:76
Method__init__
( self, num_embeddings: int, dims: int, r: int = 8, dropout: float = 0
mlx_lm/tuner/dora.py:168
Method__init__
( self, data: List[Dict[str, str]], tokenizer: PreTrainedTokenizer, text_key:
mlx_lm/tuner/datasets.py:16
Method__init__
( self, data: List[Dict[str, str]], tokenizer: PreTrainedTokenizer, chat_key:
mlx_lm/tuner/datasets.py:45
Method__init__
( self, data: List[Dict[str, str]], tokenizer: PreTrainedTokenizer, prompt_key
mlx_lm/tuner/datasets.py:93
Method__init__
(self, data: List[Any])
mlx_lm/tuner/datasets.py:137
Method__init__
(self, data: Any)
mlx_lm/tuner/datasets.py:159
Method__init__
( self, project_name: str, log_dir: str, config: dict, wrapped_callbac
mlx_lm/tuner/callbacks.py:28
Method__init__
( self, project_name: str, log_dir: str, config: dict, wrapped_callbac
mlx_lm/tuner/callbacks.py:66
Method__init__
( self, input_dims: int, output_dims: int, num_experts: int, r: int =
mlx_lm/tuner/lora.py:151
Method__init__
( self, num_embeddings: int, dims: int, r: int = 8, dropout: float = 0
mlx_lm/tuner/lora.py:250
Method__init__
(self, module)
mlx_lm/quant/gptq.py:41
Method__init__
(self, args: ModelArgs)
mlx_lm/models/telechat3.py:34
Method__init__
(self, args: ModelArgs)
mlx_lm/models/telechat3.py:104
Method__init__
(self, args: ModelArgs)
mlx_lm/models/telechat3.py:121
Method__init__
(self, args: ModelArgs)
mlx_lm/models/telechat3.py:146
Method__init__
(self, args: ModelArgs)
mlx_lm/models/qwen2.py:33
Method__init__
(self, args: ModelArgs)
mlx_lm/models/qwen2.py:99
Method__init__
(self, args: ModelArgs)
mlx_lm/models/qwen2.py:125
Method__init__
(self, args: ModelArgs)
mlx_lm/models/qwen2.py:159
Method__init__
(self, args: ModelArgs)
mlx_lm/models/ernie4_5.py:32
Method__init__
(self, args: ModelArgs)
mlx_lm/models/ernie4_5.py:95
Method__init__
(self, args: ModelArgs)
mlx_lm/models/ernie4_5.py:118
Method__init__
(self, args: ModelArgs)
mlx_lm/models/ernie4_5.py:143
Method__init__
(self)
mlx_lm/models/gpt_oss.py:63
Method__init__
(self, config: ModelArgs)
mlx_lm/models/gpt_oss.py:71
Method__init__
(self, config: ModelArgs)
mlx_lm/models/gpt_oss.py:131
Method__init__
(self, config: ModelArgs)
mlx_lm/models/gpt_oss.py:170
Method__init__
(self, args: ModelArgs)
mlx_lm/models/gpt_oss.py:193
Method__init__
(self, config: TextConfig)
mlx_lm/models/kimi_k25.py:27
Method__init__
(self, dims: int, num_heads: int, rotary_dim: int)
mlx_lm/models/phixtral.py:38
Method__init__
(self, config: ModelArgs)
mlx_lm/models/phixtral.py:114
Method__init__
(self, config: ModelArgs)
mlx_lm/models/phixtral.py:130
Method__init__
(self, config: ModelArgs)
mlx_lm/models/phixtral.py:146
Method__init__
(self, config: ModelArgs)
mlx_lm/models/phixtral.py:155
Method__init__
(self, config: ModelArgs)
mlx_lm/models/phixtral.py:165
Method__init__
(self, args: ModelArgs, layer_idx: int)
mlx_lm/models/cohere2.py:34
Method__init__
(self, args: ModelArgs, layer_idx: int)
mlx_lm/models/cohere2.py:114
Method__init__
(self, args: ModelArgs)
mlx_lm/models/cohere2.py:141
Method__init__
(self, args: ModelArgs)
mlx_lm/models/cohere2.py:185
Method__init__
(self, hidden_size: int, eps: float = 1e-6)
mlx_lm/models/qwen3_next.py:66
Method__init__
(self, args: ModelArgs)
mlx_lm/models/qwen3_next.py:82
Method__init__
(self, dim, hidden_dim)
mlx_lm/models/qwen3_next.py:162
Method__init__
(self, config: ModelArgs)
mlx_lm/models/qwen3_next.py:173
Method__init__
(self, args: ModelArgs)
mlx_lm/models/qwen3_next.py:309
Method__init__
(self, args: ModelArgs, layer_idx: int)
mlx_lm/models/qwen3_next.py:358
Method__init__
(self, args: ModelArgs)
mlx_lm/models/qwen3_next.py:393
Method__init__
( self, dims: int, eps: float = 1e-5, group: Optional[mx.distributed.Group] = None )
mlx_lm/models/minimax.py:59
Method__init__
(self, args: ModelArgs)
mlx_lm/models/minimax.py:87
Method__init__
(self, args: ModelArgs)
mlx_lm/models/minimax.py:163
Method__init__
(self, args: ModelArgs)
mlx_lm/models/minimax.py:201
Method__init__
(self, args: ModelArgs)
mlx_lm/models/minimax.py:225
Method__init__
(self, dims: int, eps: float = 1e-5)
mlx_lm/models/recurrent_gemma.py:40
Method__init__
( self, channels: int, kernel_size: int, )
mlx_lm/models/recurrent_gemma.py:80
Method__init__
( self, width: int, num_heads: int, lru_width: int = None, conv1d_temp
mlx_lm/models/recurrent_gemma.py:172
Method__init__
( self, width: int, num_heads: int, window_size: int, )
mlx_lm/models/recurrent_gemma.py:222
Method__init__
(self, width: int, expanded_width: int)
mlx_lm/models/recurrent_gemma.py:275
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