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Clean public model snapshot

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LICENSE ADDED
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+ # Upstage Solar License
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+ # Preamble
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+ The 'Upstage Solar License' (hereinafter referred to as "this License") was established by Upstage Co., Ltd., incorporated under the laws of the Republic of Korea, to encourage the development of open-source software using Solar AI models, and is not affiliated with the Apache Software Foundation.
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+ # APPENDIX: How to apply the Upstage Solar License to your work.
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+ To apply the Upstage Solar License to your work, attach the following boilerplate notice, with the fields enclosed by brackets replaced with your own identifying information. (Don't include the brackets\!) The text should be enclosed in the appropriate comment syntax for the file format. We also recommend that a file or class name and description of purpose be included on the same "printed page" as the copyright notice for easier identification within third-party archives.
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+ in Section 4(e) of the License), your model name must begin with "Solar"
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OMLX.md ADDED
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+ # Using This Quant With OMLX
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+
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+ Some OMLX builds may not yet include native Solar Open2 support in their bundled
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+ `mlx_lm` runtime. This repo includes a small compatibility patch that installs:
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+
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+ - `solar_open2.py`, the MLX loader for the Solar Open2 architecture.
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+ - `solar_open2_tool_parser.py`, a parser for Solar Open2 tool-call markup.
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+ - Tokenizer runtime detection for Solar Open2 thinking and tool-call markers.
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+ - Four-state recurrent-cache restoration for reliable multi-turn tool loops.
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+
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+ ## Install
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+
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+ Clone this model repo locally, then run the installer from the repo root:
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+
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+ ```bash
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+ sudo zsh omlx/install_omlx_solar_open2_patch.sh
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+ ```
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+
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+ The installer patches the OMLX app bundle and creates timestamped backups of any
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+ files it changes. If your OMLX installation uses a non-default location, set:
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+
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+ ```bash
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+ export OMLX_MLX_LM_DIR="/path/to/mlx_lm"
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+ export OMLX_PYTHON="/path/to/python"
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+ export OMLX_RESOURCES="/path/to/oMLX.app/Contents/Resources"
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+ sudo -E zsh omlx/install_omlx_solar_open2_patch.sh
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+ ```
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+
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+ Reload OMLX after installing the patch.
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+
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+ ## Tool Calling
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+
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+ Solar Open2 emits tool calls using this marker format:
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+
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+ ```text
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+ <|tool_call:start|>tool_name
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+ <|tool_arg:start|>argument_name<|tool_arg:value|>argument_value<|tool_arg:end|>
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+ <|tool_call:end|>
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+ ```
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+
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+ The included parser converts that format into OpenAI-compatible tool-call
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+ arguments where the serving runtime supports tool parsing.
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+
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+ ## Thinking Toggle
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+
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+ This quant defaults to clean direct responses. To enable or disable thinking in
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+ clients that pass chat-template arguments:
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+
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+ ```json
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+ {"enable_thinking": false}
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+ ```
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+
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+ ```json
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+ {"enable_thinking": true}
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+ ```
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+
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+ Advanced clients can also pass Solar's native option directly:
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+
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+ ```json
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+ {"reasoning_effort": "none"}
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+ ```
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+
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+ ```json
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+ {"reasoning_effort": "high"}
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+ ```
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+
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+ If the serving runtime does not hide reasoning channels, enabled thinking may
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+ show `<|think:start|>` and `<|think:end|>` markers in generated text.
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+
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+ ## Notes
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+
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+ OMLX updates can replace bundled runtime files. Re-run the installer after an
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+ OMLX update if the model stops loading or tool-call parsing disappears.
README.md ADDED
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+ ---
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+ language:
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+ - en
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+ - ko
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+ - ja
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+ library_name: mlx
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+ pipeline_tag: text-generation
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+ license: other
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+ license_name: upstage-solar-license
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+ license_link: LICENSE
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+ base_model: upstage/Solar-Open2-250B
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+ tags:
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+ - mlx
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+ - solar
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+ - solar-open2
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+ - moe
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+ - text-generation
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+ - quantized
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+ - 6bit
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+ ---
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+
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+ # Solar-Open2-250B-MLX-6bit
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+
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+ Built with Solar. This is an MLX 6-bit affine quantization of [upstage/Solar-Open2-250B](https://huggingface.co/upstage/Solar-Open2-250B), converted for Apple Silicon / MLX workflows.
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+
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+ ## Details
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+
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+ - Source model: `upstage/Solar-Open2-250B`
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+ - Quantization: 6-bit affine, group size 64
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+ - Local size: 190G
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+ - Weight shards: 48
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+ - Architecture: Solar Open 2 hybrid-attention MoE, 250B total / ~15B active parameters
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+ - Context: source model advertises 1M-token context; practical MLX context depends on memory and runtime settings
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+
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+ ## Important runtime notes
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+
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+ Solar Open2 is not yet a stock `mlx-lm` architecture in many installs. This repo includes `solar_open2.py`; launch with `--trust-remote-code` when serving or loading from Hugging Face.
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+
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+ ```bash
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+ mlx_lm.server \
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+ --model Vontra/Solar-Open2-250B-MLX-6bit \
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+ --host 0.0.0.0 \
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+ --port 8021 \
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+ --trust-remote-code \
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+ --temp 0.2 \
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+ --top-p 0.9 \
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+ --max-tokens 32768
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+ ```
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+
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+ You may see a `transformers` warning that mentions loading `model_type=solar_open2` into a blank model type. With the included custom MLX loader this warning is expected; the important check is that the model actually loads.
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+
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+ The tokenizer template uses Solar/Whale-style tool markers such as `<|tool_call:start|>` and `<|tool_arg:start|>`. For OpenAI-compatible tool calling, your serving runtime must parse those markers into structured `tool_calls`. Plain text generation does not need this parser.
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+
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+ ## Use with MLX
55
+
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+ This repo includes a small `solar_open2.py` MLX loader because upstream `mlx-lm` does not yet ship native Solar Open 2 support.
57
+
58
+ ```bash
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+ pip install -U mlx-lm
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+ ```
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+
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+ ```python
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+ from mlx_lm import load, generate
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+
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+ model, tokenizer = load("Vontra/Solar-Open2-250B-MLX-6bit")
66
+ prompt = "Write a short Python function that validates an IPv4 CIDR string."
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+ print(generate(model, tokenizer, prompt=prompt, max_tokens=256, verbose=True))
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+ ```
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+
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+ ## Notes
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+
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+ This is an independent community conversion under the Vontra organization. It is not an official Upstage release.
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+
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+ ## License
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+
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+ The source model is released under the Upstage Solar License. A copy is included in `LICENSE`. Please review the upstream model card and license before use or redistribution.
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+ {#- ======== Template Parameters ======== #}
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+ {%- set add_generation_prompt = add_generation_prompt if add_generation_prompt is defined else true %}
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+ {%- set provider_system_prompt = provider_system_prompt if provider_system_prompt else false %}
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+ {%- set enable_thinking = enable_thinking if enable_thinking is defined else false %}
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+ {%- set reasoning_effort = reasoning_effort if reasoning_effort is defined else ("high" if enable_thinking else "none") %}
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+ {%- set think_render_option = think_render_option if think_render_option is defined else "interleaved" %}
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+
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+ {#- ======== System Block State ======== #}
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+ {%- set sys_ns = namespace(is_first_block=true) -%}
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+
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+ {#- ======== Find last user message index ======== #}
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+ {%- set last_user_idx = namespace(value=-1) -%}
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+ {%- for message in messages -%}
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+ {%- if message.role == 'user' -%}
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+ {%- set last_user_idx.value = loop.index0 -%}
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+ {%- endif -%}
17
+ {%- endfor -%}
18
+
19
+ {#- ======== System messages renderers ======== #}
20
+ {%- macro render_system_message(user_system_messages) %}
21
+ {%- if provider_system_prompt %}
22
+ {%- if not sys_ns.is_first_block %}{{- "\n\n" }}{%- endif %}
23
+ {%- set sys_ns.is_first_block = false %}
24
+ {{- "## Provider System Prompt\n\nYou are Solar Open2 250B, a large language model trained by Upstage AI, a Korean startup. Your knowledge cutoff is 2026-02. The current date is " + strftime_now("%Y-%m-%d") + "." }}
25
+ {%- endif -%}
26
+ {%- if user_system_messages %}
27
+ {%- if not sys_ns.is_first_block %}{{- "\n\n" }}{%- endif %}
28
+ {%- set sys_ns.is_first_block = false %}
29
+ {{- "## System Prompt" }}
30
+ {%- for system_message in user_system_messages %}
31
+ {{- "\n\n" }}
32
+ {{- system_message }}
33
+ {%- endfor %}
34
+ {%- endif -%}
35
+ {%- endmacro %}
36
+
37
+ {%- macro render_tool_instruction(tools, is_last_block) %}
38
+ {%- if not sys_ns.is_first_block %}{{- "\n\n" }}{%- endif %}
39
+ {%- set sys_ns.is_first_block = false %}
40
+ {{- "## Tools\n- You may invoke one or more tools to assist with the user's query." }}
41
+ {{- "\n\n### Available Tools\n" }}
42
+ {%- for tool in tools %}
43
+ {{- "<|tool:start|>" }}
44
+ {{- tool.function | tojson }}
45
+ {{- "<|tool:end|>\n" }}
46
+ {%- endfor %}
47
+ {{- "\n### Tool Call Instruction\n" }}
48
+ {{- "- If using a tool, any reasoning must strictly precede the call. Do not append any text after the tool call.\n" }}
49
+ {{- "- If no tool is required, answer directly from your knowledge without ever mentioning the availability or absence of tools.\n" }}
50
+ {{- "- Each tool call MUST use this following format: <|tool_call:start|>{example-tool-name}\n<|tool_arg:start|>{example-key-name-1}<|tool_arg:value|>{example-value-1}<|tool_arg:end|>\n<|tool_arg:start|>{example-key-name-2}<|tool_arg:value|>{example-value-2}<|tool_arg:end|>\n<|tool_call:end|>\n" }}
51
+ {%- endmacro %}
52
+
53
+ {#-
54
+ Input convention for `response_format`:
55
+ - Per the OpenAI Chat Completions API, `response_format` is an object of one of:
56
+ {"type": "json_schema", "json_schema": {"name": ..., "schema": {...}, "strict": ...}}
57
+ {"type": "json_object"}
58
+ - Only `response_format.json_schema.schema` (the inner JSON Schema) is injected
59
+ into the prompt; the OpenAI wrapper fields (`name`, `strict`, ...) are dropped.
60
+ - For `json_object`, no schema exists, so we emit a generic JSON-only instruction.
61
+ - vLLM does NOT pass `response_format` to chat templates by default; it routes it
62
+ to guided decoding instead. This template/whale opts into prompt injection,
63
+ so callers serving the model directly via vLLM must opt in via
64
+ `chat_template_kwargs` (or rely on whale's normalization).
65
+ -#}
66
+ {%- macro render_json_response_format_instruction(response_format) %}
67
+ {%- if not sys_ns.is_first_block %}{{- "\n\n" }}{%- endif %}
68
+ {%- set sys_ns.is_first_block = false %}
69
+ {{- "## Output Format Constraint" }}
70
+ {%- if response_format.type == "json_schema" %}
71
+ {{- "\n\n- Your final response should follow the JSON schema:\n```json\n" }}
72
+ {{- response_format.json_schema.schema | tojson }}
73
+ {{- "\n```\n- Please ensure your answers adhere to this format and do not contain any unnecessary text." }}
74
+ {%- elif response_format.type == "json_object" %}
75
+ {{- "\n\n- Your final response must be a valid JSON object." }}
76
+ {{- "\n- Do not include any text outside the JSON object." }}
77
+ {%- endif %}
78
+ {%- endmacro %}
79
+
80
+ {#-
81
+ Input convention for `tool_arguments`:
82
+ - Must be a mapping (dict), NOT a JSON-encoded string.
83
+ - The OpenAI API spec defines `tool_calls[].function.arguments` as a JSON string,
84
+ but vLLM, HuggingFace transformers tool-use templates (Qwen, Hermes, Llama, ...),
85
+ and this template all expect the value to be parsed into a dict before rendering.
86
+ - vLLM normalizes this in `_postprocess_messages()` (vllm/entrypoints/chat_utils.py).
87
+ - Callers (whale, training pipelines that call `tokenizer.apply_chat_template`
88
+ directly, ...) are responsible for parsing the JSON string into a dict before
89
+ invoking the template.
90
+ -#}
91
+ {%- macro render_tool_arguments(tool_arguments) %}
92
+ {%- for args_name, args_value in tool_arguments|items %}
93
+ {{- "<|tool_arg:start|>"+ args_name + "<|tool_arg:value|>"}}
94
+ {%- set args_value = args_value if args_value is string else (args_value | tojson | safe) %}
95
+ {{- args_value }}
96
+ {{- "<|tool_arg:end|>\n" }}
97
+ {%- endfor %}
98
+ {%- endmacro %}
99
+
100
+ {#- ======== Render system message ======== #}
101
+ {%- set ns = namespace(system_messages=[]) -%}
102
+ {%- for message in messages -%}
103
+ {%- if message.role == 'system' -%}
104
+ {%- set ns.system_messages = ns.system_messages + [message.content] -%}
105
+ {%- endif -%}
106
+ {%- endfor -%}
107
+
108
+ {%- if ns.system_messages or provider_system_prompt or tools or response_format -%}
109
+ {{- "<|im:start|>system<|im:content|>" }}
110
+ {{- render_system_message(ns.system_messages) }}
111
+ {%- if tools -%}
112
+ {{- render_tool_instruction(tools, not response_format) }}
113
+ {%- endif %}
114
+ {%- if response_format -%}
115
+ {{- render_json_response_format_instruction(response_format) }}
116
+ {%- endif %}
117
+ {{- "<|im:end|>\n" }}
118
+ {%- endif -%}
119
+
120
+ {#- ======== Render main messages ======== #}
121
+ {%- for message in messages -%}
122
+ {%- if message.role == 'user' -%}
123
+ {{- "<|im:start|>user<|im:content|>" + message.content + "<|im:end|>\n" }}
124
+ {%- elif message.role == 'tool' -%}
125
+ {%- if not message.tool_call_id -%}
126
+ {{- raise_exception("tool message is missing required 'tool_call_id' field") -}}
127
+ {%- endif -%}
128
+ {%- set prev_is_tool = loop.index0 > 0 and messages[loop.index0 - 1].role == 'tool' -%}
129
+ {#- Only render at the start of a contiguous tool block; subsequent tool messages -#}
130
+ {#- are already emitted (reordered) within the first one. -#}
131
+ {%- if not prev_is_tool -%}
132
+ {%- set start_idx = loop.index0 -%}
133
+ {#- Collect contiguous tool messages starting at start_idx -#}
134
+ {%- set tool_ns = namespace(items=[], scanning=true) -%}
135
+ {%- for j in range(start_idx, messages | length) -%}
136
+ {%- if tool_ns.scanning -%}
137
+ {%- if messages[j].role == 'tool' -%}
138
+ {%- set tool_ns.items = tool_ns.items + [messages[j]] -%}
139
+ {%- else -%}
140
+ {%- set tool_ns.scanning = false -%}
141
+ {%- endif -%}
142
+ {%- endif -%}
143
+ {%- endfor -%}
144
+
145
+ {{- "<|im:start|>tool<|im:content|>" }}
146
+
147
+ {%- set prev_msg = messages[start_idx - 1] if start_idx > 0 else none -%}
148
+ {%- if prev_msg and prev_msg.role == 'assistant' and prev_msg.tool_calls -%}
149
+ {#- Render tool responses in the order of the preceding assistant's tool_calls ids. -#}
150
+ {%- set sep_ns = namespace(first=true, rendered_ids=[]) -%}
151
+ {%- for tool_call in prev_msg.tool_calls -%}
152
+ {%- for tool_msg in tool_ns.items -%}
153
+ {%- if tool_msg.tool_call_id == tool_call.id -%}
154
+ {%- if not sep_ns.first -%}{{- "\n" }}{%- endif -%}
155
+ {%- set sep_ns.first = false -%}
156
+ {%- set sep_ns.rendered_ids = sep_ns.rendered_ids + [tool_msg.tool_call_id] -%}
157
+ {{- "<|tool_response:start|>" + tool_msg.content + "<|tool_response:end|>" }}
158
+ {%- endif -%}
159
+ {%- endfor -%}
160
+ {%- endfor -%}
161
+ {#- Append any orphan tool messages (no matching id) in their original order. -#}
162
+ {%- for tool_msg in tool_ns.items -%}
163
+ {%- if tool_msg.tool_call_id not in sep_ns.rendered_ids -%}
164
+ {%- if not sep_ns.first -%}{{- "\n" }}{%- endif -%}
165
+ {%- set sep_ns.first = false -%}
166
+ {{- "<|tool_response:start|>" + tool_msg.content + "<|tool_response:end|>" }}
167
+ {%- endif -%}
168
+ {%- endfor -%}
169
+ {%- else -%}
170
+ {%- for tool_msg in tool_ns.items -%}
171
+ {%- if not loop.first -%}{{- "\n" }}{%- endif -%}
172
+ {{- "<|tool_response:start|>" + tool_msg.content + "<|tool_response:end|>" }}
173
+ {%- endfor -%}
174
+ {%- endif -%}
175
+
176
+ {{- "\n<|im:end|>\n" }}
177
+ {%- endif -%}
178
+ {%- elif message.role == 'assistant' -%}
179
+ {{- "<|im:start|>assistant<|im:content|>" }}
180
+
181
+ {#- ======== Resolve reasoning field (reasoning or reasoning_content) ======== #}
182
+ {%- if message.reasoning is defined -%}
183
+ {%- set reasoning = message.reasoning -%}
184
+ {%- elif message.reasoning_content is defined -%}
185
+ {%- set reasoning = message.reasoning_content -%}
186
+ {%- else -%}
187
+ {%- set reasoning = none -%}
188
+ {%- endif -%}
189
+
190
+ {#- ======== Assistant Thinking ======== #}
191
+ {%- if think_render_option == "preserved" -%}
192
+ {%- if reasoning -%}
193
+ {{- "<|think:start|>" + reasoning + "<|think:end|>" }}
194
+ {%- else -%}
195
+ {{- "<|think:start|><|think:end|>" }}
196
+ {%- endif -%}
197
+ {%- elif think_render_option == "interleaved" -%}
198
+ {%- if reasoning and loop.index0 > last_user_idx.value -%}
199
+ {{- "<|think:start|>" + reasoning + "<|think:end|>" }}
200
+ {%- else -%}
201
+ {{- "<|think:start|><|think:end|>" }}
202
+ {%- endif -%}
203
+ {%- endif -%}
204
+
205
+ {#- ======== Assistant Messages ======== #}
206
+ {%- if message.content -%}
207
+ {{- message.content }}
208
+ {%- endif -%}
209
+
210
+ {#- ======== Assistant Tool calls ======== #}
211
+ {%- if message.tool_calls -%}
212
+ {%- for tool_call in message.tool_calls -%}
213
+ {%- if not tool_call.id -%}
214
+ {{- raise_exception("assistant tool_call is missing required 'id' field") -}}
215
+ {%- endif -%}
216
+ {%- if not loop.first -%}{{- "\n" }}{%- endif -%}
217
+ {{- "<|tool_call:start|>" + tool_call.function.name + "\n" }}
218
+ {%- if tool_call.function.arguments is defined %}
219
+ {{- render_tool_arguments(tool_call.function.arguments) }}
220
+ {%- endif %}
221
+ {{- "<|tool_call:end|>" }}
222
+ {%- endfor -%}
223
+ {{- "\n" }}
224
+ {%- endif -%}
225
+ {{- "<|im:end|>\n" }}
226
+ {%- endif -%}
227
+ {%- endfor -%}
228
+
229
+ {%- if add_generation_prompt -%}
230
+ {%- if reasoning_effort in ["medium", "high", "xhigh"] -%}
231
+ {{- "<|im:start|>assistant<|im:content|><|think:start|>" }}
232
+ {%- else -%}
233
+ {{- "<|im:start|>assistant<|im:content|><|think:start|><|think:end|>" }}
234
+ {%- endif -%}
235
+ {%- endif -%}
config.json ADDED
@@ -0,0 +1,70 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "architectures": [
3
+ "SolarOpen2ForCausalLM"
4
+ ],
5
+ "bos_token_id": 1,
6
+ "eos_token_id": [
7
+ 2,
8
+ 129
9
+ ],
10
+ "first_k_dense_replace": 0,
11
+ "gqa_interval": 3,
12
+ "gqa_layers": [
13
+ 0,
14
+ 4,
15
+ 8,
16
+ 12,
17
+ 16,
18
+ 20,
19
+ 24,
20
+ 28,
21
+ 32,
22
+ 36,
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+ 40,
24
+ 44
25
+ ],
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+ "head_dim": 128,
27
+ "hidden_size": 4096,
28
+ "intermediate_size": 10240,
29
+ "kda_allow_neg_eigval": true,
30
+ "kda_use_full_proj": false,
31
+ "linear_attn_config": {
32
+ "short_conv_kernel_size": 4,
33
+ "head_dim": 128,
34
+ "num_heads": 64,
35
+ "num_kv_heads": null
36
+ },
37
+ "max_position_embeddings": 1048576,
38
+ "model_type": "solar_open2",
39
+ "moe_intermediate_size": 1280,
40
+ "n_routed_experts": 320,
41
+ "n_shared_experts": 1,
42
+ "norm_topk_prob": true,
43
+ "num_attention_heads": 64,
44
+ "num_experts_per_tok": 8,
45
+ "num_hidden_layers": 48,
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+ "num_key_value_heads": 8,
47
+ "pad_token_id": 2,
48
+ "partial_rotary_factor": 1.0,
49
+ "quantization": {
50
+ "group_size": 64,
51
+ "bits": 6,
52
+ "mode": "affine"
53
+ },
54
+ "quantization_config": {
55
+ "group_size": 64,
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+ "bits": 6,
57
+ "mode": "affine"
58
+ },
59
+ "rms_norm_eps": 1e-05,
60
+ "rope_theta": 10000,
61
+ "routed_scaling_factor": 1.0,
62
+ "tie_word_embeddings": false,
63
+ "torch_dtype": "bfloat16",
64
+ "transformers_version": "5.5.4",
65
+ "use_gqa_gate": true,
66
+ "use_rope": false,
67
+ "vocab_size": 196608,
68
+ "model_file": "solar_open2.py",
69
+ "library_name": "mlx"
70
+ }
generation_config.json ADDED
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+ {
2
+ "bos_token_id": 1,
3
+ "do_sample": true,
4
+ "eos_token_id": [
5
+ 2,
6
+ 129
7
+ ],
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+ "transformers_version": "4.57.6"
9
+ }
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