llama : add Command-R support (#6033)
Information about the Command-R 35B model (128k context) can be found at: https://huggingface.co/CohereForAI/c4ai-command-r-v01 Based on the llama2 model with a few changes: 1) New hyper parameter to scale output logits (logit_scale) 2) Uses LayerNorm instead of RMSNorm 3) Transfomer layers have a single shared LayerNorm that feeds into both the self-attention and FFN layers in parallel. There is no post-attention LayerNorm. 4) No support for Rotary Position Embeddings (RoPE) scaling 5) No biases used Find GGUF files here: https://huggingface.co/andrewcanis/c4ai-command-r-v01-GGUF To convert model to GGUF format yourself: 1) Download Command-R Hugging Face safetensors: git lfs install git clone https://huggingface.co/CohereForAI/c4ai-command-r-v01 2) Run: python3 convert-hf-to-gguf.py --outtype f16 ./c4ai-command-r-v01
This commit is contained in:
parent
4e9a7f7f7f
commit
12247f4c69
5 changed files with 219 additions and 0 deletions
|
@ -42,6 +42,7 @@ class Keys:
|
|||
EXPERT_COUNT = "{arch}.expert_count"
|
||||
EXPERT_USED_COUNT = "{arch}.expert_used_count"
|
||||
POOLING_TYPE = "{arch}.pooling_type"
|
||||
LOGIT_SCALE = "{arch}.logit_scale"
|
||||
|
||||
class Attention:
|
||||
HEAD_COUNT = "{arch}.attention.head_count"
|
||||
|
@ -121,6 +122,7 @@ class MODEL_ARCH(IntEnum):
|
|||
GEMMA = auto()
|
||||
STARCODER2 = auto()
|
||||
MAMBA = auto()
|
||||
COMMAND_R = auto()
|
||||
|
||||
|
||||
class MODEL_TENSOR(IntEnum):
|
||||
|
@ -187,6 +189,7 @@ MODEL_ARCH_NAMES: dict[MODEL_ARCH, str] = {
|
|||
MODEL_ARCH.GEMMA: "gemma",
|
||||
MODEL_ARCH.STARCODER2: "starcoder2",
|
||||
MODEL_ARCH.MAMBA: "mamba",
|
||||
MODEL_ARCH.COMMAND_R: "command-r",
|
||||
}
|
||||
|
||||
TENSOR_NAMES: dict[MODEL_TENSOR, str] = {
|
||||
|
@ -579,6 +582,18 @@ MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = {
|
|||
MODEL_TENSOR.SSM_D,
|
||||
MODEL_TENSOR.SSM_OUT,
|
||||
],
|
||||
MODEL_ARCH.COMMAND_R: [
|
||||
MODEL_TENSOR.TOKEN_EMBD,
|
||||
MODEL_TENSOR.OUTPUT_NORM,
|
||||
MODEL_TENSOR.ATTN_NORM,
|
||||
MODEL_TENSOR.ATTN_Q,
|
||||
MODEL_TENSOR.ATTN_K,
|
||||
MODEL_TENSOR.ATTN_V,
|
||||
MODEL_TENSOR.ATTN_OUT,
|
||||
MODEL_TENSOR.FFN_GATE,
|
||||
MODEL_TENSOR.FFN_DOWN,
|
||||
MODEL_TENSOR.FFN_UP,
|
||||
],
|
||||
# TODO
|
||||
}
|
||||
|
||||
|
|
|
@ -361,6 +361,9 @@ class GGUFWriter:
|
|||
def add_clamp_kqv(self, value: float) -> None:
|
||||
self.add_float32(Keys.Attention.CLAMP_KQV.format(arch=self.arch), value)
|
||||
|
||||
def add_logit_scale(self, value: float) -> None:
|
||||
self.add_float32(Keys.LLM.LOGIT_SCALE.format(arch=self.arch), value)
|
||||
|
||||
def add_expert_count(self, count: int) -> None:
|
||||
self.add_uint32(Keys.LLM.EXPERT_COUNT.format(arch=self.arch), count)
|
||||
|
||||
|
|
Loading…
Add table
Add a link
Reference in a new issue