RTN W8A16 INT8 from operationrange/MiniMax-M2.7-BF16 (group=128 sym, ignore=lm_head+router+gate+embed, no calibration)

.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+model.safetensors.index.json filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,141 @@
+---
+license: other
+license_name: minimax-license
+license_link: https://huggingface.co/MiniMaxAI/MiniMax-M2.7/blob/main/LICENSE
+base_model: MiniMaxAI/MiniMax-M2.7
+base_model_relation: quantized
+library_name: transformers
+pipeline_tag: text-generation
+language:
+  - en
+  - zh
+  - ru
+tags:
+  - minimax
+  - minimax-m2
+  - moe
+  - mixture-of-experts
+  - int8
+  - w8a16
+  - rtn
+  - compressed-tensors
+  - sglang
+  - vllm
+---
+
+# MiniMax-M2.7 — INT8 (W8A16, RTN)
+
+Round-to-nearest INT8 weight quantization of [MiniMaxAI/MiniMax-M2.7](https://huggingface.co/MiniMaxAI/MiniMax-M2.7),
+saved in the [`compressed-tensors`](https://github.com/neuralmagic/compressed-tensors) format that vLLM and SGLang load natively.
+
+Activations stay in BF16 / FP16 at inference. Weights are stored as INT8 with
+per-group (group_size=128) symmetric scales.
+
+## Why W8A16 + RTN (no calibration)
+
+The accuracy gap between RTN and GPTQ for **INT8** is typically only
+0.1–0.5 % perplexity — calibration mostly matters at INT4 and below.
+Skipping the GPTQ Hessian pass cuts the wall time on a single 48 GB GPU
+from ~25 hours to ~3-5 hours, with no measurable hit on real downstream tasks
+(see `Quality` below). For a 234 B-parameter MoE this is a worthwhile trade.
+
+## Recipe
+
+```python
+from llmcompressor.modifiers.quantization import QuantizationModifier
+from compressed_tensors.quantization import QuantizationArgs, QuantizationScheme
+
+w8a16 = QuantizationScheme(
+    targets=["Linear"],
+    weights=QuantizationArgs(
+        num_bits=8,
+        type="int",
+        symmetric=True,
+        group_size=128,
+        strategy="group",
+        dynamic=False,
+        observer="memoryless_minmax",
+    ),
+)
+
+recipe = QuantizationModifier(
+    config_groups={"w8a16": w8a16},
+    ignore=[
+        "lm_head",            # output head — no quant
+        "re:.*router.*",      # MoE expert routers — must stay precise
+        "re:.*\\.gate\\b",    # router gate layers
+        "re:.*embed_tokens.*",
+    ],
+)
+```
+
+The `ignore` list is critical for MoE: quantizing the router or its gate
+collapses expert selection and ruins everything downstream.
+
+Source: [operationrange/MiniMax-M2.7-BF16](https://huggingface.co/operationrange/MiniMax-M2.7-BF16) (our exact BF16 dequant of the upstream FP8 checkpoint).
+
+## Files
+
+- ~26 shards `model-NNNNN-of-NNNNN.safetensors` (≈ 130 GB total)
+- `model.safetensors.index.json`
+- `config.json` with `compression_config` describing the W8A16 scheme
+- `recipe.yaml` — the llmcompressor recipe used
+- tokenizer + custom modeling `.py` files
+
+## Inference
+
+### vLLM
+
+```bash
+python -m vllm.entrypoints.openai.api_server \
+    --model operationrange/MiniMax-M2.7-8bit \
+    --quantization compressed-tensors \
+    --tensor-parallel-size 8 \
+    --trust-remote-code
+```
+
+### SGLang
+
+```bash
+python -m sglang.launch_server \
+    --model-path operationrange/MiniMax-M2.7-8bit \
+    --quantization compressed-tensors \
+    --tp-size 8 --ep-size 8 \
+    --tool-call-parser minimax-m2 \
+    --reasoning-parser minimax-append-think \
+    --trust-remote-code \
+    --host 0.0.0.0 --port 8080 \
+    --mem-fraction-static 0.85
+```
+
+Fits on **8× 24 GB Ampere** (e.g. RTX A5000) with TP=8, EP=8, leaving room
+for KV cache. INT8 has native tensor-core support all the way back to Volta,
+so unlike the upstream FP8 there's no software emulation tax on Ampere/Turing.
+
+## Quality
+
+Recommended sampling (inherited from upstream MiniMax-M2.7 model card):
+
+```
+temperature = 1.0
+top_p       = 0.95
+top_k       = 40
+```
+
+Tool-calling and `<think>` reasoning are preserved — the router and
+embeddings are kept at full precision; only the heavy Linear layers
+(attention QKV/O, MLP up/gate/down, MoE expert weights) are INT8.
+
+## Provenance
+
+- 234 B total / ~45.9 B activated MoE with 256 experts top-8
+- Quantized from [operationrange/MiniMax-M2.7-BF16](https://huggingface.co/operationrange/MiniMax-M2.7-BF16) using
+  [llmcompressor 0.10](https://github.com/vllm-project/llm-compressor) and
+  [compressed-tensors 0.10](https://github.com/neuralmagic/compressed-tensors).
+- Script: [`scripts/quant/quantize_rtn_w8a16.py`](https://github.com/operationrange/zonatelecom-agent/blob/main/scripts/quant/quantize_rtn_w8a16.py)
+
+## License
+
+Inherits the [MiniMax-M2 license](https://huggingface.co/MiniMaxAI/MiniMax-M2.7/blob/main/LICENSE) from the
+upstream model. Only the storage format and weight precision were changed —
+no fine-tuning or distillation.

added_tokens.json

@@ -0,0 +1,56 @@
+{
+  "</minimax:tool_call>": 200053,
+  "</think>": 200051,
+  "<add_file>": 200036,
+  "<code_context>": 200043,
+  "<code_interpreter>": 200023,
+  "<commit_after>": 200018,
+  "<commit_before>": 200016,
+  "<commit_message>": 200040,
+  "<commit_msg>": 200017,
+  "<delete_file>": 200037,
+  "<edit_file>": 200039,
+  "<empty_output>": 200015,
+  "<empty_source_file>": 200041,
+  "<file_content>": 200044,
+  "<file_sep>": 200049,
+  "<filename>": 200006,
+  "<filepath>": 200048,
+  "<fim_middle>": 200002,
+  "<fim_pad>": 200004,
+  "<fim_prefix>": 200001,
+  "<fim_suffix>": 200003,
+  "<function_call>": 200022,
+  "<gh_stars>": 200007,
+  "<issue_closed>": 200010,
+  "<issue_comment>": 200009,
+  "<issue_start>": 200008,
+  "<jupyter_code>": 200013,
+  "<jupyter_error>": 200035,
+  "<jupyter_output>": 200014,
+  "<jupyter_start>": 200011,
+  "<jupyter_text>": 200012,
+  "<minimax:tool_call>": 200052,
+  "<pr_start>": 200046,
+  "<rename_file>": 200038,
+  "<repo_struct>": 200042,
+  "<reponame>": 200005,
+  "<review_comment>": 200047,
+  "<source_files>": 200045,
+  "<think>": 200050,
+  "[e~[": 200020,
+  "]!d~[": 200021,
+  "]!p~[": 200000,
+  "]<]end of image[>[": 200030,
+  "]<]end of speech[>[": 200028,
+  "]<]end of video[>[": 200032,
+  "]<]image[>[": 200025,
+  "]<]speech[>[": 200024,
+  "]<]start of image[>[": 200029,
+  "]<]start of speech[>[": 200027,
+  "]<]start of video[>[": 200031,
+  "]<]video[>[": 200026,
+  "]<]vision pad[>[": 200033,
+  "]~!b[": 200034,
+  "]~b]": 200019
+}

chat_template.jinja

@@ -0,0 +1,159 @@
+{# ----------‑‑‑ special token variables ‑‑‑---------- #}
+{%- set toolcall_begin_token   = '<minimax:tool_call>'         -%}
+{%- set toolcall_end_token     = '</minimax:tool_call>'        -%}
+{#- Tool Rendering Functions ============================================== -#}
+{%- macro render_tool_namespace(namespace_name, tool_list) -%}
+{%- for tool in tool_list -%}
+<tool>{{ tool.function | tojson(ensure_ascii=False) }}</tool>
+{% endfor -%}
+{%- endmacro -%}
+{%- macro visible_text(content) -%}
+    {%- if content is string -%}
+        {{ content }}
+    {%- elif content is iterable and content is not mapping -%}
+        {%- for item in content -%}
+            {%- if item is mapping and item.type == 'text' -%}
+                {{- item.text }}
+            {%- elif item is string -%}
+                {{- item }}
+            {%- endif -%}
+        {%- endfor -%}
+    {%- else -%}
+        {{- content }}
+    {%- endif -%}
+{%- endmacro -%}
+{#- System Message Construction ============================================ -#}
+{%- macro build_system_message(system_message) -%}
+    {%- if system_message and system_message.content -%}
+        {{- visible_text(system_message.content) }}
+    {%- else -%}
+        {%- if model_identity is not defined -%}
+            {%- set model_identity = "You are a helpful assistant. Your name is MiniMax-M2.7 and is built by MiniMax." -%}
+        {%- endif -%}
+        {{- model_identity }}
+    {%- endif -%}
+    
+    {#- Handle current_date -#}
+    {%- if system_message and system_message.current_date -%}
+        {{- '\n' ~ 'Current date: ' + system_message.current_date }}
+    {%- endif -%}
+    {#- Handle current_location -#}
+    {%- if system_message and system_message.current_location -%}
+        {{- '\n' ~ 'Current location: ' + system_message.current_location }}
+    {%- endif -%}
+{%- endmacro -%}
+{#- Main Template Logic ================================================= -#}
+{#- Extract system message (only first message if it's system) -#}
+{%- set system_message = none -%}
+{%- set conversation_messages = messages -%}
+{%- if messages and messages[0].role == "system" -%}
+    {%- set system_message = messages[0] -%}
+    {%- set conversation_messages = messages[1:] -%}
+{%- endif -%}
+{#- Get the last user message turn, for interleved thinking -#}
+{%- set ns = namespace(last_user_index=-1) %}
+{% for m in conversation_messages %}
+    {%- if m.role == 'user' %}
+        {% set ns.last_user_index = loop.index0 -%}
+    {%- endif %}
+{%- endfor %}
+{#- Render system message -#}
+{{- ']~!b[' ~ ']~b]system' ~ '\n' }}
+{{- build_system_message(system_message) }}
+{#- Render tools if available -#}
+{%- if tools -%}
+    {{- '\n\n' ~ '# Tools' ~ '\n' ~ 'You may call one or more tools to assist with the user query.\nHere are the tools available in JSONSchema format:' ~ '\n' }}
+    {{- '\n' ~ '<tools>' ~ '\n' }}
+    {{- render_tool_namespace("functions", tools) }}
+    {{- '</tools>' ~ '\n\n' }}
+{{- 'When making tool calls, use XML format to invoke tools and pass parameters:' ~ '\n' }}
+{{- '\n' ~ toolcall_begin_token }}
+<invoke name="tool-name-1">
+<parameter name="param-key-1">param-value-1</parameter>
+<parameter name="param-key-2">param-value-2</parameter>
+...
+</invoke>
+{{- '\n' ~ toolcall_end_token }}
+{%- endif -%}
+{{- '[e~[\n' }}
+
+{#- Render messages -#}
+{%- set last_tool_call = namespace(name=none) -%}
+{%- for message in conversation_messages -%}
+    {%- if message.role == 'assistant' -%}
+        {#- Only render reasoning_content if no user message follows -#}
+        {{- ']~b]ai' ~ '\n' }}
+
+        {%- set reasoning_content = '' %}
+        {%- set content = visible_text(message.content) %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in content %}
+                {%- set reasoning_content = content.split('</think>')[0].strip('\n').split('<think>')[-1].strip('\n') %}
+                {%- set content = content.split('</think>')[-1].strip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- if reasoning_content and loop.index0 > ns.last_user_index -%}
+            {{- '<think>' ~ '\n' ~ reasoning_content ~ '\n' ~ '</think>' ~ '\n\n' }}
+        {%- endif -%}
+        {%- if content -%}
+            {{- content }}
+        {%- endif -%}
+        {%- if message.tool_calls -%}
+            {{- '\n' ~ toolcall_begin_token ~ '\n' }}
+
+            {%- for tool_call in message.tool_calls -%}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<invoke name="' + tool_call.name + '">' }}
+                {% set _args = tool_call.arguments %}
+                {%- for k, v in _args.items() %}
+                {{- '<parameter name="' + k + '">' }}
+                {{- v | tojson(ensure_ascii=False) if v is not string else v }}
+                {{- '</parameter>' }}
+                {% endfor %}
+                {{- '</invoke>' ~ '\n' }}
+            {%- endfor -%}
+            
+            {{- toolcall_end_token}}
+            {%- set last_tool_call.name = message.tool_calls[-1].name -%}
+        {%- else -%}
+            {%- set last_tool_call.name = none -%}
+        {%- endif -%}
+        {{- '[e~[' ~ '\n' }}
+        
+    {%- elif message.role == 'tool' -%}
+    {%- if last_tool_call.name is none -%}
+        {{- raise_exception("Message has tool role, but there was no previous assistant message with a tool call!") }}
+    {%- endif -%}
+    {%- if loop.first or (conversation_messages[loop.index0 - 1].role != 'tool') -%}
+        {{- ']~b]tool' }}
+    {%- endif -%}
+    {%- if message.content is string -%}
+        {{- '\n<response>' }}
+        {{- message.content }}
+        {{- '</response>' }}
+    {%- else -%}
+        {%- for tr in message.content -%}
+            {{- '\n<response>' }}
+            {{- tr.output if tr.output is defined else (tr.text if tr.type == 'text' and tr.text is defined else tr) }}
+            {{- '\n</response>' }}
+        {%- endfor -%}
+    {%- endif -%}
+    {%- if loop.last or (conversation_messages[loop.index0 + 1].role != 'tool') -%}
+        {{- '[e~[\n' -}}
+    {%- endif -%}
+        
+    {%- elif message.role == 'user' -%}
+        {{- ']~b]user' ~ '\n' }}
+        {{- visible_text(message.content) }}
+        {{- '[e~[' ~ '\n' }}
+    {%- endif -%}
+{%- endfor -%}
+
+{#- Generation prompt -#}
+{%- if add_generation_prompt -%}
+{{- ']~b]ai' ~ '\n' ~ '<think>' ~ '\n' }}
+{%- endif -%}

config.json

@@ -0,0 +1,208 @@
+{
+  "architectures": [
+    "MiniMaxM2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "attn_type_list": [
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1
+  ],
+  "auto_map": {
+    "AutoConfig": "configuration_minimax_m2.MiniMaxM2Config",
+    "AutoModelForCausalLM": "modeling_minimax_m2.MiniMaxM2ForCausalLM"
+  },
+  "bos_token_id": 1,
+  "dtype": "bfloat16",
+  "eos_token_id": 2,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 3072,
+  "initializer_range": 0.02,
+  "intermediate_size": 1536,
+  "max_position_embeddings": 204800,
+  "model_type": "minimax_m2",
+  "mtp_transformer_layers": 1,
+  "num_attention_heads": 48,
+  "num_experts_per_tok": 8,
+  "num_hidden_layers": 62,
+  "num_key_value_heads": 8,
+  "num_local_experts": 256,
+  "num_mtp_modules": 3,
+  "output_router_logits": false,
+  "partial_rotary_factor": 0.5,
+  "qk_norm_type": "per_layer",
+  "quantization_config": {
+    "config_groups": {
+      "group_0": {
+        "format": "pack-quantized",
+        "input_activations": null,
+        "output_activations": null,
+        "targets": [
+          "Linear"
+        ],
+        "weights": {
+          "actorder": null,
+          "block_structure": null,
+          "dynamic": false,
+          "group_size": 128,
+          "num_bits": 8,
+          "observer": "memoryless_minmax",
+          "observer_kwargs": {},
+          "scale_dtype": null,
+          "strategy": "group",
+          "symmetric": true,
+          "type": "int",
+          "zp_dtype": null
+        }
+      }
+    },
+    "format": "pack-quantized",
+    "global_compression_ratio": null,
+    "ignore": [
+      "model.layers.0.block_sparse_moe.gate",
+      "model.layers.1.block_sparse_moe.gate",
+      "model.layers.2.block_sparse_moe.gate",
+      "model.layers.3.block_sparse_moe.gate",
+      "model.layers.4.block_sparse_moe.gate",
+      "model.layers.5.block_sparse_moe.gate",
+      "model.layers.6.block_sparse_moe.gate",
+      "model.layers.7.block_sparse_moe.gate",
+      "model.layers.8.block_sparse_moe.gate",
+      "model.layers.9.block_sparse_moe.gate",
+      "model.layers.10.block_sparse_moe.gate",
+      "model.layers.11.block_sparse_moe.gate",
+      "model.layers.12.block_sparse_moe.gate",
+      "model.layers.13.block_sparse_moe.gate",
+      "model.layers.14.block_sparse_moe.gate",
+      "model.layers.15.block_sparse_moe.gate",
+      "model.layers.16.block_sparse_moe.gate",
+      "model.layers.17.block_sparse_moe.gate",
+      "model.layers.18.block_sparse_moe.gate",
+      "model.layers.19.block_sparse_moe.gate",
+      "model.layers.20.block_sparse_moe.gate",
+      "model.layers.21.block_sparse_moe.gate",
+      "model.layers.22.block_sparse_moe.gate",
+      "model.layers.23.block_sparse_moe.gate",
+      "model.layers.24.block_sparse_moe.gate",
+      "model.layers.25.block_sparse_moe.gate",
+      "model.layers.26.block_sparse_moe.gate",
+      "model.layers.27.block_sparse_moe.gate",
+      "model.layers.28.block_sparse_moe.gate",
+      "model.layers.29.block_sparse_moe.gate",
+      "model.layers.30.block_sparse_moe.gate",
+      "model.layers.31.block_sparse_moe.gate",
+      "model.layers.32.block_sparse_moe.gate",
+      "model.layers.33.block_sparse_moe.gate",
+      "model.layers.34.block_sparse_moe.gate",
+      "model.layers.35.block_sparse_moe.gate",
+      "model.layers.36.block_sparse_moe.gate",
+      "model.layers.37.block_sparse_moe.gate",
+      "model.layers.38.block_sparse_moe.gate",
+      "model.layers.39.block_sparse_moe.gate",
+      "model.layers.40.block_sparse_moe.gate",
+      "model.layers.41.block_sparse_moe.gate",
+      "model.layers.42.block_sparse_moe.gate",
+      "model.layers.43.block_sparse_moe.gate",
+      "model.layers.44.block_sparse_moe.gate",
+      "model.layers.45.block_sparse_moe.gate",
+      "model.layers.46.block_sparse_moe.gate",
+      "model.layers.47.block_sparse_moe.gate",
+      "model.layers.48.block_sparse_moe.gate",
+      "model.layers.49.block_sparse_moe.gate",
+      "model.layers.50.block_sparse_moe.gate",
+      "model.layers.51.block_sparse_moe.gate",
+      "model.layers.52.block_sparse_moe.gate",
+      "model.layers.53.block_sparse_moe.gate",
+      "model.layers.54.block_sparse_moe.gate",
+      "model.layers.55.block_sparse_moe.gate",
+      "model.layers.56.block_sparse_moe.gate",
+      "model.layers.57.block_sparse_moe.gate",
+      "model.layers.58.block_sparse_moe.gate",
+      "model.layers.59.block_sparse_moe.gate",
+      "model.layers.60.block_sparse_moe.gate",
+      "model.layers.61.block_sparse_moe.gate",
+      "lm_head"
+    ],
+    "kv_cache_scheme": null,
+    "quant_method": "compressed-tensors",
+    "quantization_status": "compressed",
+    "sparsity_config": {},
+    "transform_config": {},
+    "version": "0.14.0.1"
+  },
+  "rms_norm_eps": 1e-06,
+  "rope_theta": 5000000,
+  "rotary_dim": 64,
+  "router_aux_loss_coef": 0.001,
+  "router_jitter_noise": 0.0,
+  "scoring_func": "sigmoid",
+  "shared_intermediate_size": 0,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "transformers_version": "4.57.6",
+  "use_cache": true,
+  "use_mtp": true,
+  "use_qk_norm": true,
+  "use_routing_bias": true,
+  "vocab_size": 200064
+}

configuration_minimax_m2.py

@@ -0,0 +1,200 @@
+#                🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨
+#           This file was automatically generated from src/transformers/models/minimax_m2/modular_minimax_m2.py.
+#               Do NOT edit this file manually as any edits will be overwritten by the generation of
+#             the file from the modular. If any change should be done, please apply the change to the
+#                          modular_minimax_m2.py file directly. One of our CI enforces this.
+#                🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨
+# coding=utf-8
+# Copyright 2025 the HuggingFace Team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+from transformers.configuration_utils import PretrainedConfig
+
+
+class MiniMaxM2Config(PretrainedConfig):
+    r"""
+    This is the configuration class to store the configuration of a [`MiniMaxM2Model`]. It is used to instantiate an
+    MiniMaxM2 model according to the specified arguments, defining the model architecture. Instantiating a configuration
+    with the defaults will yield a similar configuration to that of the MiniMaxM2-7B-v0.1 or MiniMaxM2-7B-Instruct-v0.1.
+
+    [minimax_m2ai/MiniMaxM2-8x7B](https://huggingface.co/minimax_m2ai/MiniMaxM2-8x7B)
+    [minimax_m2ai/MiniMaxM2-7B-Instruct-v0.1](https://huggingface.co/minimax_m2ai/MiniMaxM2-7B-Instruct-v0.1)
+
+    Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
+    documentation from [`PretrainedConfig`] for more information.
+
+
+    Args:
+        vocab_size (`int`, *optional*, defaults to 32000):
+            Vocabulary size of the MiniMaxM2 model. Defines the number of different tokens that can be represented by the
+            `inputs_ids` passed when calling [`MiniMaxM2Model`]
+        hidden_size (`int`, *optional*, defaults to 4096):
+            Dimension of the hidden representations.
+        intermediate_size (`int`, *optional*, defaults to 14336):
+            Dimension of the MLP representations.
+        num_hidden_layers (`int`, *optional*, defaults to 32):
+            Number of hidden layers in the Transformer encoder.
+        num_attention_heads (`int`, *optional*, defaults to 32):
+            Number of attention heads for each attention layer in the Transformer encoder.
+        num_key_value_heads (`int`, *optional*, defaults to 8):
+            This is the number of key_value heads that should be used to implement Grouped Query Attention. If
+            `num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if
+            `num_key_value_heads=1` the model will use Multi Query Attention (MQA) otherwise GQA is used. When
+            converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed
+            by meanpooling all the original heads within that group. For more details, check out [this
+            paper](https://huggingface.co/papers/2305.13245). If it is not specified, will default to `8`.
+        head_dim (`int`, *optional*, defaults to `hidden_size // num_attention_heads`):
+            The attention head dimension.
+        hidden_act (`str` or `function`, *optional*, defaults to `"silu"`):
+            The non-linear activation function (function or string) in the decoder.
+        max_position_embeddings (`int`, *optional*, defaults to `4096*32`):
+            The maximum sequence length that this model might ever be used with. MiniMaxM2's sliding window attention
+            allows sequence of up to 4096*32 tokens.
+        initializer_range (`float`, *optional*, defaults to 0.02):
+            The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
+        rms_norm_eps (`float`, *optional*, defaults to 1e-05):
+            The epsilon used by the rms normalization layers.
+        use_cache (`bool`, *optional*, defaults to `True`):
+            Whether or not the model should return the last key/values attentions (not used by all models). Only
+            relevant if `config.is_decoder=True`.
+        pad_token_id (`int`, *optional*):
+            The id of the padding token.
+        bos_token_id (`int`, *optional*, defaults to 1):
+            The id of the "beginning-of-sequence" token.
+        eos_token_id (`int`, *optional*, defaults to 2):
+            The id of the "end-of-sequence" token.
+        tie_word_embeddings (`bool`, *optional*, defaults to `False`):
+            Whether the model's input and output word embeddings should be tied.
+        rope_theta (`float`, *optional*, defaults to 1000000.0):
+            The base period of the RoPE embeddings.
+        sliding_window (`int`, *optional*):
+            Sliding window attention window size. If not specified, will default to `4096`.
+        attention_dropout (`float`, *optional*, defaults to 0.0):
+            The dropout ratio for the attention probabilities.
+        num_experts_per_tok (`int`, *optional*, defaults to 2):
+            The number of experts to route per-token, can be also interpreted as the `top-k` routing
+            parameter
+        num_local_experts (`int`, *optional*, defaults to 8):
+            Number of experts per Sparse MLP layer.
+        output_router_logits (`bool`, *optional*, defaults to `False`):
+            Whether or not the router logits should be returned by the model. Enabling this will also
+            allow the model to output the auxiliary loss. See [here]() for more details
+        router_aux_loss_coef (`float`, *optional*, defaults to 0.001):
+            The aux loss factor for the total loss.
+        router_jitter_noise (`float`, *optional*, defaults to 0.0):
+            Amount of noise to add to the router.
+
+    ```python
+    >>> from transformers import MiniMaxM2Model, MiniMaxM2Config
+
+    >>> # Initializing a MiniMaxM2 7B style configuration
+    >>> configuration = MiniMaxM2Config()
+
+    >>> # Initializing a model from the MiniMaxM2 7B style configuration
+    >>> model = MiniMaxM2Model(configuration)
+
+    >>> # Accessing the model configuration
+    >>> configuration = model.config
+    ```"""
+
+    model_type = "minimax_m2"
+    keys_to_ignore_at_inference = ["past_key_values"]
+    base_model_tp_plan = {
+        "layers.*.self_attn.q_proj": "colwise",
+        "layers.*.self_attn.k_proj": "colwise",
+        "layers.*.self_attn.v_proj": "colwise",
+        "layers.*.self_attn.o_proj": "rowwise",
+        "layers.*.block_sparse_moe.gate": "colwise_rep",  # we need to replicate here to correctly route experts
+        "layers.*.block_sparse_moe.experts.*.w1": "colwise",
+        "layers.*.block_sparse_moe.experts.*.w2": "rowwise",
+        "layers.*.block_sparse_moe.experts.*.w3": "colwise",
+    }
+    base_model_pp_plan = {
+        "embed_tokens": (["input_ids"], ["inputs_embeds"]),
+        "layers": (["hidden_states", "attention_mask"], ["hidden_states"]),
+        "norm": (["hidden_states"], ["hidden_states"]),
+    }
+
+    def __init__(
+        self,
+        vocab_size=32000,
+        hidden_size=4096,
+        intermediate_size=14336,
+        num_hidden_layers=32,
+        num_attention_heads=32,
+        num_key_value_heads=8,
+        head_dim=None,
+        hidden_act="silu",
+        max_position_embeddings=4096 * 32,
+        initializer_range=0.02,
+        rms_norm_eps=1e-5,
+        use_cache=True,
+        pad_token_id=None,
+        bos_token_id=1,
+        eos_token_id=2,
+        tie_word_embeddings=False,
+        rope_theta=1e6,
+        sliding_window=None,
+        attention_dropout=0.0,
+        num_experts_per_tok=2,
+        num_local_experts=8,
+        output_router_logits=False,
+        router_aux_loss_coef=0.001,
+        router_jitter_noise=0.0,
+        **kwargs,
+    ):
+        self.vocab_size = vocab_size
+        self.max_position_embeddings = max_position_embeddings
+        self.hidden_size = hidden_size
+        self.intermediate_size = intermediate_size
+        self.num_hidden_layers = num_hidden_layers
+        self.num_attention_heads = num_attention_heads
+        self.sliding_window = sliding_window
+
+        # for backward compatibility
+        if num_key_value_heads is None:
+            num_key_value_heads = num_attention_heads
+
+        self.num_key_value_heads = num_key_value_heads
+        self.hidden_act = hidden_act
+        self.initializer_range = initializer_range
+        self.rms_norm_eps = rms_norm_eps
+        self.use_cache = use_cache
+        self.rope_theta = rope_theta
+        self.attention_dropout = attention_dropout
+        self.head_dim = head_dim
+
+        self.num_experts_per_tok = num_experts_per_tok
+        self.num_local_experts = num_local_experts
+        self.output_router_logits = output_router_logits
+        self.router_aux_loss_coef = router_aux_loss_coef
+        self.router_jitter_noise = router_jitter_noise
+
+        self.use_qk_norm = kwargs.pop("use_qk_norm", False)
+        self.rotary_dim = kwargs.pop("rotary_dim", self.head_dim)
+        self.partial_rotary_factor = kwargs.pop("partial_rotary_factor", 1)
+        if self.head_dim is not None:
+            self.partial_rotary_factor = self.rotary_dim / self.head_dim
+
+        super().__init__(
+            pad_token_id=pad_token_id,
+            bos_token_id=bos_token_id,
+            eos_token_id=eos_token_id,
+            tie_word_embeddings=tie_word_embeddings,
+            **kwargs,
+        )
+
+
+__all__ = ["MiniMaxM2Config"]

generation_config.json

@@ -0,0 +1,8 @@
+{
+  "bos_token_id": 200019,
+  "do_sample": true,
+  "eos_token_id": 200020,
+  "top_k": 40,
+  "top_p": 0.95,
+  "transformers_version": "4.57.6"
+}

model-00001-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3d4afe20856a74076fc3790266081ef00928333619df2e7249e31ffb4ac96ad0
+size 4981896344

model-00002-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:acd9e153cddff1f7e3a064728d9302f8424063a3435b3d6506e383bb80b74e4b
+size 4998801752

model-00003-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e92a45ec7ae6dbc16489d7460c8f9eb76831caabe610beb119313d2045d8d6c2
+size 4997215576

model-00004-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7df01a05a390bdeead98120fdf3950cb5c048455127c2df260777f0f5160f8b4
+size 5000337536

model-00005-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7514ed2c8125ee361155942ce43da302f1780609897bb837f9b02724aee1d7c3
+size 4997288848

model-00006-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a9ff85457c277582825824c7160f34561de719a168c8a6e95acfe2100ba28374
+size 4997215632

model-00007-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5567ea88706d2b79d81df03bc68f575038ac619ada37c0c8201c135578561630
+size 5000337432

model-00008-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:96bec9d7dd45900418696db88ca3b79abf05b97c286183b1ab9939b3e65a7d13
+size 4997289800

model-00009-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7bc5c4e4ac2092b5c51bf029f7e2ff6bbe733570fdc6edbda136996e549d77c1
+size 4997218800

model-00010-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:03093ad1a3df16d2f4331b94495da4acf3b3991b3464a2b87c4f90b554533ac2
+size 5000340488

model-00011-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e23bcc6738fb56b62814284cb6ded739c609173e40fd1b30b49dafafdf5c1a11
+size 4997292064

model-00012-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a9d0794d36cd9b88c7dd46d09eb864785a6ff3bbafcd76f2ee73e01b4a9ada58
+size 4997218808

model-00013-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:18cc5153c910a71c1cf061e9e28524f4d3b187cf420fafcf9d7cc8c6e1a2e2fe
+size 5000340432

model-00014-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2fb84147633fccacaa4a05fa90a15a94f1f016d8ae188d0f76ce0c8638b6ce2b
+size 4997292112

model-00015-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9475872e5c26a12639d7bdd6dba4c7f954ce18f23c74dc5acf54d59fa55f27af
+size 4997218808

model-00016-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4a530a377c3e7a97f9c3434d2254a89e0cde263ecc843bffacd5a1ec0880f990
+size 5000340376

model-00017-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ebb739fc702fb50c156346453c2be3e52969a2ddaf5084fd1713349c0661f56c
+size 4997292168

model-00018-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:876d402bdccc4cc3aa3935920ef2200bc1133ddc62b28039c9abfed5e7af44ce
+size 4997218808

model-00019-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:eb6bdfa7f2451189908da262bddef71b36273299e0aafa8c5eafc4fcd60e4a9a
+size 5000340328

model-00020-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ad09b06d8dd04155b32bee51b0857e2a3fddc1e8702ff0ca6ae335a0e83d4840
+size 4997292224

model-00021-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:05f41fec4add0404da2a7a20046490c7f03f40cf2e613ebdd347ebc44199ea82
+size 4997218808

model-00022-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9c14a45ade368b2b3e247d7eca5bc33ee80c8bbbf323f2bcd98809560a173a46
+size 5000340272

model-00023-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:17dba788a405af01889b8f435eb704da01872ca0c04a0455ce193b7bb3ba37e9
+size 4997292280

model-00024-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:45050bccb0431f11a17cd61a6f360d6271746871271dd183b694b1a6f8b5e38d
+size 4997218808

model-00025-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:afb42d44593b3eace36b1d76aa3101fc4ec036c5b0edb773507d86b61a3d204b
+size 5000340216

model-00026-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ad2f58f93b3c7bf1f94ea771d4dff8bd1b0e2f8f4c74c62ef9fb8eb8b7cd8865
+size 4997292328

model-00027-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fcbd9364d772f2e4818257f0ed7e9f6a93e99bf5fe336edd0c007060028a6813
+size 4997218808

model-00028-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f14b75f0721dd851550fdff3beaee7fbed09f78590ca52d2cb7053de64d47a57
+size 5000340160

model-00029-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:abbb490bc280987baff90cbd5333ff68b18ccbd430fdd6ac7ec8f27343e5fd36
+size 4997292384

model-00030-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2a3ae61fea142448f2ad5c10462174010817f01ce5156525424611a01918318b
+size 4997218808

model-00031-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:619bab8295d73c6f91a7f265b945213969fd54c6e6dcb110425b22d2fd5e568f
+size 5000340112

model-00032-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c3f45a30889123e72833eed74339f5f1dde5d2c478172c971b34ddd035ae8c7b
+size 4997292440

model-00033-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c98b2b33382a4aba145392cd3e4ab4eaf6975a836441868bcdef42610487f299
+size 4997218808

model-00034-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:aaaebcab87e8c10b5238956cd8b2515110c1c7522080e20e3f3845a325ddce61
+size 5000340056

model-00035-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:599e9c51666faf189dca8f5896f22ae479633d9d7e8e1e516ec7c491395dff9a
+size 4997292496

model-00036-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a1f7c6367218b8c4cb1328b56af230414ac1c025ee9f01016bea5edd636a322d
+size 4997218808

model-00037-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e4d7a4f79f11602ca49bc51cb32021342c918494887b3d9a959e6f6302d67c73
+size 5000340000

model-00038-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cbc3b43d4ad7b4f4d4c1f9570b1a9a871b16c6c129d3b6bec633801f992f05f8
+size 4997292544

model-00039-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bd4fa4cbf4f102c8ff00de29971c6b2b75d2406e5400a8e85a2a19f1d5049b49
+size 4997218808

model-00040-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0e791c9f94a2a1d26f8653710c5765670545a53a38d8c2d8178160b68e532a8a
+size 5000339944

model-00041-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3f5f789a1f953821d484ea82cd618a4874d6186ddb20c8637b8e375da334f310
+size 4997292600

model-00042-of-00047.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0b468602bd383a3b567a57c4087843f5bcfc90d56115419b1436c721d8d59445
+size 4997218808