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1 change: 1 addition & 0 deletions convert-hf-to-gguf-update.py
Original file line number Diff line number Diff line change
Expand Up @@ -84,6 +84,7 @@ class TOKENIZER_TYPE(IntEnum):
{"name": "jina-v2-de", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-de", },
{"name": "smaug-bpe", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/abacusai/Smaug-Llama-3-70B-Instruct", },
{"name": "jina-v2-code", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-code", },
{"name": "jais", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/core42/jais-13b", },
]


Expand Down
85 changes: 76 additions & 9 deletions convert-hf-to-gguf.py
Original file line number Diff line number Diff line change
Expand Up @@ -421,9 +421,6 @@ def get_vocab_base_pre(self, tokenizer) -> str:
# NOTE: if you get an error here, you need to update the convert-hf-to-gguf-update.py script
# or pull the latest version of the model from Huggingface
# don't edit the hashes manually!
if chkhsh == "0ef9807a4087ebef797fc749390439009c3b9eda9ad1a097abbe738f486c01e5":
# ref: https://huggingface.co/meta-llama/Meta-Llama-3-8B
res = "llama-bpe"
if chkhsh == "049ecf7629871e3041641907f3de7c733e4dbfdc736f57d882ba0b0845599754":
# ref: https://huggingface.co/deepseek-ai/deepseek-llm-7b-base
res = "deepseek-llm"
Expand Down Expand Up @@ -451,18 +448,12 @@ def get_vocab_base_pre(self, tokenizer) -> str:
if chkhsh == "6221ad2852e85ce96f791f476e0b390cf9b474c9e3d1362f53a24a06dc8220ff":
# ref: https://huggingface.co/smallcloudai/Refact-1_6-base
res = "refact"
if chkhsh == "9c2227e4dd922002fb81bde4fc02b0483ca4f12911410dee2255e4987644e3f8":
# ref: https://huggingface.co/CohereForAI/c4ai-command-r-v01
res = "command-r"
if chkhsh == "e636dc30a262dcc0d8c323492e32ae2b70728f4df7dfe9737d9f920a282b8aea":
# ref: https://huggingface.co/Qwen/Qwen1.5-7B
res = "qwen2"
if chkhsh == "b6dc8df998e1cfbdc4eac8243701a65afe638679230920b50d6f17d81c098166":
# ref: https://huggingface.co/allenai/OLMo-1.7-7B-hf
res = "olmo"
if chkhsh == "a8594e3edff7c29c003940395316294b2c623e09894deebbc65f33f1515df79e":
# ref: https://huggingface.co/databricks/dbrx-base
res = "dbrx"
if chkhsh == "0876d13b50744004aa9aeae05e7b0647eac9d801b5ba4668afc01e709c15e19f":
# ref: https://huggingface.co/jinaai/jina-embeddings-v2-base-en
res = "jina-v2-en"
Expand All @@ -478,6 +469,9 @@ def get_vocab_base_pre(self, tokenizer) -> str:
if chkhsh == "7967bfa498ade6b757b064f31e964dddbb80f8f9a4d68d4ba7998fcf281c531a":
# ref: https://huggingface.co/jinaai/jina-embeddings-v2-base-code
res = "jina-v2-code"
if chkhsh == "b53802fb28e26d645c3a310b34bfe07da813026ec7c7716883404d5e0f8b1901":
# ref: https://huggingface.co/core42/jais-13b
res = "jais"

if res is None:
logger.warning("\n")
Expand Down Expand Up @@ -2713,6 +2707,79 @@ def write_tensors(self):
if len(experts) > 0:
raise ValueError(f"Unprocessed experts: {experts}")

@Model.register("JAISLMHeadModel")
class JaisModel(Model):
model_arch = gguf.MODEL_ARCH.JAIS

def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)

# SwigLU activation
assert self.hparams["activation_function"] == "swiglu"
# ALiBi position embedding
assert self.hparams["position_embedding_type"] == "alibi"

# Embeddings scale
self.embeddings_scale = 1.0
# note: For some JAIS flavors, output is tied to (same as) wte in original model
self.output_is_wte = False
if 'mup_embeddings_scale' in self.hparams:
self.output_is_wte = True # Hack (?)
self.embeddings_scale = self.hparams['mup_embeddings_scale']
elif 'embeddings_scale' in self.hparams:
self.embeddings_scale = self.hparams['embeddings_scale']
else:
assert False

self.width_scale = 1.0
if 'mup_output_alpha' in self.hparams:
assert 'mup_width_scale' in self.hparams
self.width_scale = self.hparams['mup_output_alpha'] * self.hparams['mup_width_scale']
elif 'width_scale' in self.hparams:
self.width_scale = self.hparams['width_scale']
else:
assert False

def set_vocab(self):
self._set_vocab_gpt2()

def set_gguf_parameters(self):
self.gguf_writer.add_name(self.dir_model.name)
self.gguf_writer.add_block_count(self.hparams["n_layer"])
self.gguf_writer.add_context_length(self.hparams["n_positions"])
self.gguf_writer.add_embedding_length(self.hparams["n_embd"])
self.gguf_writer.add_feed_forward_length(self.hparams["n_inner"])
self.gguf_writer.add_head_count(self.hparams["n_head"])
self.gguf_writer.add_layer_norm_eps(self.hparams["layer_norm_epsilon"])
self.gguf_writer.add_file_type(self.ftype)

def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
del bid # unused

tensors: list[tuple[str, Tensor]] = []

# we don't need these
if name.endswith((".attn.bias", "relative_pe.slopes")):
return tensors

if name.endswith((".c_attn.weight", ".c_proj.weight", ".c_fc.weight", ".c_fc2.weight")):
data_torch = data_torch.transpose(1, 0)

new_name = self.map_tensor_name(name)

if new_name == self.format_tensor_name(gguf.MODEL_TENSOR.TOKEN_EMBD):
tensors.append((new_name, data_torch * self.embeddings_scale))
if self.output_is_wte:
tensors.append((self.format_tensor_name(gguf.MODEL_TENSOR.OUTPUT), data_torch * self.width_scale))
elif new_name == self.format_tensor_name(gguf.MODEL_TENSOR.OUTPUT):
assert not self.output_is_wte
tensors.append((new_name, data_torch * self.width_scale))
else:
tensors.append((new_name, data_torch))

return tensors



###### CONVERSION LOGIC ######

Expand Down
1 change: 0 additions & 1 deletion examples/main/main.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -716,7 +716,6 @@ int main(int argc, char ** argv) {

// Console/Stream Output
fprintf(stdout, "%s", token_str.c_str());

// Record Displayed Tokens To Log
// Note: Generated tokens are created one by one hence this check
if (embd.size() > 1) {
Expand Down
2 changes: 1 addition & 1 deletion ggml.c
Original file line number Diff line number Diff line change
Expand Up @@ -13954,13 +13954,13 @@ static void ggml_compute_forward_soft_max_f32(
} else {
for (int i = 0; i < nc; ++i) {
wp[i] += slope*mp_f32[i];

}
}
}

#ifndef NDEBUG
for (int i = 0; i < nc; ++i) {
//printf("p[%d] = %f\n", i, p[i]);
assert(!isnan(wp[i]));
}
#endif
Expand Down
14 changes: 14 additions & 0 deletions gguf-py/gguf/constants.py
Original file line number Diff line number Diff line change
Expand Up @@ -148,6 +148,7 @@ class MODEL_ARCH(IntEnum):
OLMO = auto()
ARCTIC = auto()
DEEPSEEK2 = auto()
JAIS = auto()


class MODEL_TENSOR(IntEnum):
Expand Down Expand Up @@ -236,6 +237,7 @@ class MODEL_TENSOR(IntEnum):
MODEL_ARCH.OLMO: "olmo",
MODEL_ARCH.ARCTIC: "arctic",
MODEL_ARCH.DEEPSEEK2: "deepseek2",
MODEL_ARCH.JAIS: "jais",
}

TENSOR_NAMES: dict[MODEL_TENSOR, str] = {
Expand Down Expand Up @@ -807,6 +809,18 @@ class MODEL_TENSOR(IntEnum):
MODEL_TENSOR.FFN_DOWN_SHEXP,
MODEL_TENSOR.FFN_UP_SHEXP,
],
MODEL_ARCH.JAIS: [
MODEL_TENSOR.TOKEN_EMBD,
MODEL_TENSOR.OUTPUT_NORM,
MODEL_TENSOR.OUTPUT,
MODEL_TENSOR.ATTN_NORM,
MODEL_TENSOR.ATTN_QKV,
MODEL_TENSOR.ATTN_OUT,
MODEL_TENSOR.FFN_NORM,
MODEL_TENSOR.FFN_DOWN,
MODEL_TENSOR.FFN_GATE,
MODEL_TENSOR.FFN_UP,
],
# TODO
}

Expand Down
19 changes: 10 additions & 9 deletions gguf-py/gguf/tensor_mapping.py
Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@ class TensorNameMap:
# Token embeddings
MODEL_TENSOR.TOKEN_EMBD: (
"gpt_neox.embed_in", # gptneox
"transformer.wte", # gpt2 gpt-j mpt refact qwen dbrx
"transformer.wte", # gpt2 gpt-j mpt refact qwen dbrx jais
"transformer.word_embeddings", # falcon
"word_embeddings", # bloom
"model.embed_tokens", # llama-hf
Expand Down Expand Up @@ -48,7 +48,7 @@ class TensorNameMap:
# Output
MODEL_TENSOR.OUTPUT: (
"embed_out", # gptneox
"lm_head", # gpt2 mpt falcon llama-hf baichuan qwen mamba dbrx
"lm_head", # gpt2 mpt falcon llama-hf baichuan qwen mamba dbrx jais
"output", # llama-pth bloom internlm2
"word_embeddings_for_head", # persimmon
"lm_head.linear", # phi2
Expand All @@ -57,7 +57,7 @@ class TensorNameMap:
# Output norm
MODEL_TENSOR.OUTPUT_NORM: (
"gpt_neox.final_layer_norm", # gptneox
"transformer.ln_f", # gpt2 gpt-j falcon
"transformer.ln_f", # gpt2 gpt-j falcon jais
"model.norm", # llama-hf baichuan internlm2
"norm", # llama-pth
"transformer.norm_f", # mpt dbrx
Expand All @@ -80,7 +80,7 @@ class TensorNameMap:
# Attention norm
MODEL_TENSOR.ATTN_NORM: (
"gpt_neox.layers.{bid}.input_layernorm", # gptneox
"transformer.h.{bid}.ln_1", # gpt2 gpt-j refact qwen
"transformer.h.{bid}.ln_1", # gpt2 gpt-j refact qwen jais
"transformer.blocks.{bid}.norm_1", # mpt
"transformer.h.{bid}.input_layernorm", # falcon7b
"h.{bid}.input_layernorm", # bloom
Expand Down Expand Up @@ -108,7 +108,7 @@ class TensorNameMap:
# Attention query-key-value
MODEL_TENSOR.ATTN_QKV: (
"gpt_neox.layers.{bid}.attention.query_key_value", # gptneox
"transformer.h.{bid}.attn.c_attn", # gpt2 qwen
"transformer.h.{bid}.attn.c_attn", # gpt2 qwen jais
"transformer.blocks.{bid}.attn.Wqkv", # mpt
"transformer.blocks.{bid}.norm_attn_norm.attn.Wqkv", # dbrx
"transformer.h.{bid}.self_attention.query_key_value", # falcon
Expand Down Expand Up @@ -159,7 +159,7 @@ class TensorNameMap:
# Attention output
MODEL_TENSOR.ATTN_OUT: (
"gpt_neox.layers.{bid}.attention.dense", # gptneox
"transformer.h.{bid}.attn.c_proj", # gpt2 refact qwen
"transformer.h.{bid}.attn.c_proj", # gpt2 refact qwen jais
"transformer.blocks.{bid}.attn.out_proj", # mpt
"transformer.h.{bid}.self_attention.dense", # falcon
"h.{bid}.self_attention.dense", # bloom
Expand Down Expand Up @@ -197,7 +197,7 @@ class TensorNameMap:
# Feed-forward norm
MODEL_TENSOR.FFN_NORM: (
"gpt_neox.layers.{bid}.post_attention_layernorm", # gptneox
"transformer.h.{bid}.ln_2", # gpt2 refact qwen
"transformer.h.{bid}.ln_2", # gpt2 refact qwen jais
"h.{bid}.post_attention_layernorm", # bloom
"transformer.blocks.{bid}.norm_2", # mpt
"model.layers.{bid}.post_attention_layernorm", # llama-hf
Expand All @@ -224,7 +224,7 @@ class TensorNameMap:
# Feed-forward up
MODEL_TENSOR.FFN_UP: (
"gpt_neox.layers.{bid}.mlp.dense_h_to_4h", # gptneox
"transformer.h.{bid}.mlp.c_fc", # gpt2
"transformer.h.{bid}.mlp.c_fc", # gpt2 jais
"transformer.blocks.{bid}.ffn.up_proj", # mpt
"transformer.h.{bid}.mlp.dense_h_to_4h", # falcon
"h.{bid}.mlp.dense_h_to_4h", # bloom
Expand Down Expand Up @@ -270,6 +270,7 @@ class TensorNameMap:
"model.layers.{bid}.mlp.gate_proj", # llama-hf refact
"layers.{bid}.feed_forward.w1", # llama-pth
"transformer.h.{bid}.mlp.w2", # qwen
"transformer.h.{bid}.mlp.c_fc2", # jais
"model.layers.layers.{bid}.mlp.gate_proj", # plamo
"model.layers.{bid}.feed_forward.w1", # internlm2
"encoder.layers.{bid}.mlp.fc12", # nomic-bert
Expand All @@ -293,7 +294,7 @@ class TensorNameMap:
# Feed-forward down
MODEL_TENSOR.FFN_DOWN: (
"gpt_neox.layers.{bid}.mlp.dense_4h_to_h", # gptneox
"transformer.h.{bid}.mlp.c_proj", # gpt2 refact qwen
"transformer.h.{bid}.mlp.c_proj", # gpt2 refact qwen jais
"transformer.blocks.{bid}.ffn.down_proj", # mpt
"transformer.h.{bid}.mlp.dense_4h_to_h", # falcon
"h.{bid}.mlp.dense_4h_to_h", # bloom
Expand Down
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