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Add architectures #29

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f73209b
architecture files
vaahtio May 16, 2024
b069edb
updated types with new values
vaahtio May 16, 2024
7c5d353
fix: minor fixes to arch templates
bergr7 May 21, 2024
fdb411c
fix: trust remote code for _load_config
bergr7 May 21, 2024
22654d8
updated read me
vaahtio May 27, 2024
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6 changes: 6 additions & 0 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -172,6 +172,12 @@ Currently `flow-merge` supports most of the popular and proven merge methods.
| `qwen` | `QwenForCausalLM` |
| `mistral` | `MistralForCausalLM` |
| `llama` | `LlamaForCausalLM` |
| `gemma` | `GemmaForCausalLM` |
| `phi` | `PhiForCausalLM` |
| `phi3` | `Phi3ForCausalLM` |




> 📢 _We plan to support many models and architectures more, including encoder models such as BERT-Family models too._

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72 changes: 72 additions & 0 deletions flow_merge/data/architectures/gemma.json
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{
"model_type": "gemma",
"architectures": [
"GemmaForCausalLM"
],
"num_layers_config_key": "num_hidden_layers",
"weights": [
{
"name": "model.embed_tokens.weight",
"type": "embed_tokens",
"layer_type": "embedding"
},
{
"name": "model.layers.{layer_index}.input_layernorm.weight",
"type": "input_layernorm",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.self_attn.q_proj.weight",
"type": "self_attn",
"projection": "q_proj",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.self_attn.k_proj.weight",
"type": "self_attn",
"projection": "k_proj",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.self_attn.v_proj.weight",
"type": "self_attn",
"projection": "v_proj",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.self_attn.o_proj.weight",
"type": "self_attn",
"projection": "o_proj",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.post_attention_layernorm.weight",
"type": "post_attention_layernorm",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.mlp.gate_proj.weight",
"type": "mlp",
"projection": "gate_proj",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.mlp.up_proj.weight",
"type": "mlp",
"projection": "up_proj",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.mlp.down_proj.weight",
"type": "mlp",
"projection": "down_proj",
"layer_type": "decoder"
},
{
"name": "model.norm.weight",
"type": "norm",
"layer_type": "post_norm"
}
],
"residual": {}
}
117 changes: 117 additions & 0 deletions flow_merge/data/architectures/phi.json
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{
"model_type": "phi",
"architectures": [
"PhiForCausalLM"
],
"num_layers_config_key": "num_hidden_layers",
"weights": [
{
"name": "model.embed_tokens.weight",
"type": "embed_tokens",
"layer_type": "embedding"
},
{
"name": "model.layers.{layer_index}.input_layernorm.weight",
"type": "input_layernorm",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.input_layernorm.bias",
"type": "input_layernorm",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.self_attn.q_proj.weight",
"type": "self_attn",
"projection": "q_proj",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.self_attn.q_proj.bias",
"type": "self_attn",
"projection": "q_proj",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.self_attn.k_proj.weight",
"type": "self_attn",
"projection": "k_proj",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.self_attn.k_proj.bias",
"type": "self_attn",
"projection": "k_proj",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.self_attn.v_proj.weight",
"type": "self_attn",
"projection": "v_proj",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.self_attn.v_proj.bias",
"type": "self_attn",
"projection": "v_proj",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.self_attn.dense.weight",
"type": "self_attn",
"projection": "dense",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.self_attn.dense.bias",
"type": "self_attn",
"projection": "dense",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.mlp.fc1.weight",
"type": "mlp",
"projection": "fc1",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.mlp.fc1.bias",
"type": "mlp",
"projection": "fc1",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.mlp.fc2.weight",
"type": "mlp",
"projection": "fc2",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.mlp.fc2.bias",
"type": "mlp",
"projection": "fc2",
"layer_type": "decoder"
},
{
"name": "model.final_layernorm.weight",
"type": "final_layernorm",
"layer_type": "layernorm"
},
{
"name": "model.final_layernorm.bias",
"type": "final_layernorm",
"layer_type": "layernorm"
},
{
"name": "lm_head.weight",
"type": "lm_head",
"layer_type": "head"
},
{
"name": "lm_head.bias",
"type": "lm_head",
"layer_type": "head"
}
],
"residual": {}
}
59 changes: 59 additions & 0 deletions flow_merge/data/architectures/phi3.json
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{
"model_type": "phi3",
"architectures": [
"Phi3ForCausalLM"
],
"num_layers_config_key": "num_hidden_layers",
"weights": [
{
"name": "model.embed_tokens.weight",
"type": "embed_tokens",
"layer_type": "embedding"
},
{
"name": "model.layers.{layer_index}.input_layernorm.weight",
"type": "input_layernorm",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.self_attn.o_proj.weight",
"type": "self_attn",
"projection": "o_proj",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.self_attn.qkv_proj.weight",
"type": "self_attn",
"projection": "qkv_proj",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.mlp.gate_up_proj.weight",
"type": "mlp",
"projection": "gate_up_proj",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.mlp.down_proj.weight",
"type": "mlp",
"projection": "down_proj",
"layer_type": "decoder"
},
{
"name": "model.layers.{layer_index}.post_attention_layernorm.weight",
"type": "post_attention_layernorm",
"layer_type": "decoder"
},
{
"name": "model.norm.weight",
"type": "norm",
"layer_type": "post_norm"
},
{
"name": "lm_head.weight",
"type": "lm_head",
"layer_type": "head"
}
],
"residual": {}
}
11 changes: 6 additions & 5 deletions flow_merge/lib/architecture.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,9 +10,9 @@
import flow_merge.data.architectures

ArchitectureType = Enum(
"ArchitectureType", ["MistralForCausalLM", "LlamaForCausalLM", "Qwen2ForCausalLM"]
"ArchitectureType", ["MistralForCausalLM", "LlamaForCausalLM", "Qwen2ForCausalLM", "PhiForCausalLM", "Phi3ForCausalLM"]
)
ModelType = Enum("ModelType", ["mistral", "llama", "qwen-1.5"])
ModelType = Enum("ModelType", ["mistral", "llama", "qwen-1.5", "phi", "phi3"])
ModelWeightType = Enum(
"ModelWeightType",
[
Expand All @@ -22,15 +22,16 @@
"embed_tokens",
"norm",
"lm_head",
"post_attention_layernorm",
"post_attention_layernorm",
"final_layernorm",
],
)
ProjectionType = Enum(
"ProjectionType",
["v_proj", "q_proj", "k_proj", "o_proj", "gate_proj", "up_proj", "down_proj"],
["v_proj", "q_proj", "k_proj", "o_proj", "gate_proj", "up_proj", "down_proj", "dense", "fc1", "fc2", "qkv_proj", "gate_up_proj"],
)
ModelWeightLayerType = Enum(
"ModelWeightLayerType", ["decoder", "embedding", "head", "post_norm"]
"ModelWeightLayerType", ["decoder", "embedding", "head", "post_norm", "layernorm"]
)


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14 changes: 7 additions & 7 deletions flow_merge/lib/merge_config.py
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Expand Up @@ -132,8 +132,8 @@ def __init__(
self.directory_settings: DirectorySettings = data.directory_settings
self.hf_hub_settings: HfHubSettings = data.hf_hub_settings
self.device = self.select_device()
self.models: List[Model] = self.create_models()
self.base_model: Model = self.create_base_model()
self.models: List[Model] = self.create_models(trust_remote_code=self.hf_hub_settings.trust_remote_code)
self.base_model: Model = self.create_base_model(trust_remote_code=self.hf_hub_settings.trust_remote_code)
self.method_config = self._extract_and_set_weights()

@staticmethod
Expand Down Expand Up @@ -171,18 +171,18 @@ def select_device(self) -> str:
return "cpu"
return device

def create_models(self) -> List[Model]:
def create_models(self, trust_remote_code: bool) -> List[Model]:
# observe that models list doesn't contain the base_model by design
# access base_model: Model by accessing base_model variable
models_data = [
m for m in self.data.models if m.path_or_id != self.data.base_model
]
return [Model.from_path(model_data.path_or_id) for model_data in models_data]
return [Model.from_path(model_data.path_or_id, trust_remote_code=trust_remote_code) for model_data in models_data] # TODO - this should take trust_remote_code

def create_base_model(self) -> Model:
def create_base_model(self, trust_remote_code: bool) -> Model:
if not self.data.base_model:
first_model_from_list = self.data.models[0]
return Model.from_path(first_model_from_list.path_or_id)
return Model.from_path(first_model_from_list.path_or_id, trust_remote_code=trust_remote_code) # TODO - this should take trust_remote_code
else:
base_model = next(
(
Expand All @@ -197,7 +197,7 @@ def create_base_model(self) -> Model:
f"Base model '{self.data.base_model}' not found in the list of "
+ f"models {[model.path_or_id for model in self.data.models]}."
)
return Model.from_path(base_model.path_or_id)
return Model.from_path(base_model.path_or_id, trust_remote_code=trust_remote_code)

def _extract_and_set_weights(
self,
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