dahara1/gemma-4-E2B-it-assistant_gguf overview

---

license: apache-2.0

language:

• ja
• en

base_model:

• google/gemma-4-E2B-it-assistant

tags:

• gguf
• llama.cpp
• mtp
• gemma4

---

Gemma4は小さいモデルに先行させる事で推論を高速化するMTP(Multi-Token Prediction)という仕組みがあります。

このモデルはdahara1/gemma-4-E2B-it-UD-japanese-imatrixをMTPで動かすための小モデルです。

Gemma4 has a mechanism called MTP (Multi-Token Prediction) that speeds up inference by running a smaller model ahead of it.

This model is a small model for running dahara1/gemma-4-E2B-it-UD-japanese-imatrix using MTP.

llama-server command example

./llama-server   \
-m ./gemma-4-E2B-it-UD-Q4_K_XL.gguf    \
--host 0.0.0.0   \
--port 8080   \
--temp 1.0   \
--top-p 0.95   \
--top-k 64   \
--min-p 0.0  \
 --ctx-size 32000   \
--flash-attn on   \
--jinja   \
--model-draft ./gemma-4-E2B-it-assistant_gguf/Gemma-4-E2B-It-Assistant-77M-Q8_0.gguf   \
--chat-template-file ./gemma-4-E2B-it-assistant_gguf/chat_template.jinja   \
--spec-type draft-mtp   \
--reasoning on

mtp_bench.py
  code_python        pred= 192 draft= 225 acc= 114 rate=0.507 tok/s=190.4
  code_cpp           pred= 192 draft= 207 acc= 121 rate=0.585 tok/s=209.9
  explain_concept    pred= 192 draft= 239 acc= 110 rate=0.460 tok/s=184.7
  summarize          pred= 192 draft= 190 acc= 127 rate=0.668 tok/s=227.4
  qa_factual         pred= 192 draft= 210 acc= 120 rate=0.571 tok/s=208.4
  translation        pred= 192 draft= 222 acc= 116 rate=0.522 tok/s=198.1
  creative_short     pred= 192 draft= 219 acc= 116 rate=0.530 tok/s=197.9
  stepwise_math      pred= 192 draft= 197 acc= 125 rate=0.634 tok/s=220.4
  long_code_review   pred= 192 draft= 207 acc= 121 rate=0.585 tok/s=204.3

Aggregate: {
  "n_requests": 9,
  "total_predicted": 1728,
  "total_draft": 1916,
  "total_draft_accepted": 1070,
  "aggregate_accept_rate": 0.5585,
  "wall_s_total": 9.14
}


mtp_bench_jp.py
  code_python        pred= 192 draft= 178 acc= 131 rate=0.736 tok/s=240.6
  code_cpp           pred= 192 draft= 196 acc= 124 rate=0.633 tok/s=219.3
  explain_concept    pred= 192 draft= 212 acc= 120 rate=0.566 tok/s=207.4
  summarize          pred= 192 draft= 180 acc= 130 rate=0.722 tok/s=238.1
  qa_factual         pred= 192 draft= 191 acc= 127 rate=0.665 tok/s=227.3
  translation        pred= 192 draft= 221 acc= 117 rate=0.529 tok/s=199.9
  creative_short     pred= 192 draft= 219 acc= 117 rate=0.534 tok/s=200.4
  stepwise_math      pred= 192 draft= 195 acc= 125 rate=0.641 tok/s=221.1
  long_code_review   pred= 192 draft= 226 acc= 115 rate=0.509 tok/s=188.0

Aggregate: {
  "n_requests": 9,
  "total_predicted": 1728,
  "total_draft": 1818,
  "total_draft_accepted": 1106,
  "aggregate_accept_rate": 0.6084,
  "wall_s_total": 8.52
}