Duplicate from nesilabs/Nesi2

Co-authored-by: Ricardo Sanchez <neorichi@users.noreply.huggingface.co>

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Nesi2-Q6_K-mtp.gguf

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README.md

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+---
+license: apache-2.0
+language:
+  - en
+tags:
+  - cybersecurity
+  - pentesting
+  - security
+  - uncensored
+  - tool-calling
+  - gguf
+  - llama-cpp
+pipeline_tag: text-generation
+---
+
+# Nesi2 — Uncensored AI for Cybersecurity (GGUF / llama.cpp)
+
+**Nesi2** is an uncensored large language model, curated and optimized by
+**Nesilabs** specifically for **offensive and defensive cybersecurity**:
+penetration testing, vulnerability analysis, exploit development, secure
+code review, and audit automation.
+
+It is packaged by Nesilabs as a **GGUF** build for **llama.cpp**, so it runs on a
+single GPU without an AWQ/vLLM stack. This is the build we run as an autonomous
+**pentest agent**: it reliably reaches code-exec on multi-stage targets
+(web → WebSocket tool abuse → RCE) with native tool-calling.
+
+## Highlights
+- **Unrestricted** for legitimate security use cases.
+- **~27B parameters**, long context (up to **240k tokens** in production), native tool-calling.
+- Two GGUF builds: **Q8_0** (≈lossless, production quality) and **Q6_K** (lighter).
+- Ships the **MTP** draft weights (`*-mtp*.gguf`) for optional speculative decode.
+- Validated end-to-end as a **pentest agent** (live RCE + loot + flag on a 3-stage CTF).
+
+## Model details
+| | |
+|---|---|
+| Format | **GGUF** (llama.cpp) |
+| Quantizations | **Q8_0** (~29 GB) · **Q6_K** (~22 GB) |
+| Context length | up to 262,144 tokens (240k used in prod) |
+| Tool-calling | OpenAI-compatible (native in llama.cpp `llama-server`) |
+| Serving | **llama.cpp `llama-server`** (OpenAI `/v1` compatible) |
+| KV cache | bf16 by default; `q8_0` to roughly halve footprint |
+
+> Note: the Hub's "Architecture" widget reads the GGUF's internal loader tag
+> (`general.architecture`); that is only a llama.cpp loader key baked into the
+> file and does not reflect the model name. The model is **Nesi2**.
+
+## Files
+| File | What |
+|---|---|
+| `Nesi2-Q8_0.gguf` | the model, **Q8_0** (max quality) |
+| `Nesi2-mtp-Q8_0.gguf` | MTP draft head for Q8 (optional, `--model-draft`) |
+| `Nesi2-Q6_K.gguf` | the model, **Q6_K** (lighter) |
+| `Nesi2-Q6_K-mtp.gguf` | Q6_K with the MTP head already merged (single file) |
+
+---
+
+## Two configurations
+
+Both serve the same `nesi2` model over an OpenAI-compatible `/v1`. Pick by VRAM
+and quality target.
+
+| Config | Files | VRAM (weights + MTP) | When |
+|---|---|---|---|
+| **A — Q8_0 + MTP** | `Nesi2-Q8_0.gguf` + `Nesi2-mtp-Q8_0.gguf` | ~29 + ~3 GB | max quality, 96 GB card |
+| **B — Q6_K (+MTP)** | `Nesi2-Q6_K.gguf` (or `Nesi2-Q6_K-mtp.gguf`) | ~22 GB | lighter, more slots / smaller card |
+
+> **MTP (speculative decode)** needs a llama.cpp build that supports
+> `--spec-type draft-mtp`. It helps **single-stream latency**; under heavy
+> concurrency it did not improve aggregate throughput in our tests, so for
+> multi-user serving you can run without it and keep it for low-latency use.
+
+---
+
+## Deploy on a GPU box from zero
+
+Everything below runs **on the GPU box as root**. The gateway bits run on your
+LiteLLM host. Target image: `nvidia/cuda:12.8.1-devel-ubuntu22.04`, ≥ 60 GB disk
+(≥ 90 GB if you want Q8 **and** Q6 on the same box).
+
+### 0) Pick a GPU
+| GPU | VRAM | Fits | single-stream tok/s (240k slot) |
+|---|---|---|---|
+| RTX A6000 | 48 GB | 1 user @ 240k (Q6_K) | ~22 |
+| RTX PRO 6000 **Max-Q** (power-capped ~300W) | 96 GB | 1–3 users @ 240k | ~20–25 (gateway end-to-end) |
+| RTX PRO 6000 **WS** (full ~600W) | 96 GB | up to 5 users @ 240k (Q8+MTP) | **~55** |
+
+> Blackwell (PRO 6000, `sm_120`) needs CUDA toolkit **≥ 12.8**; build llama.cpp
+> with `-DCMAKE_CUDA_ARCHITECTURES=120`. On Ampere (A6000) use `86`.
+
+### 1) Deps + build llama.cpp
+```bash
+export DEBIAN_FRONTEND=noninteractive
+apt-get update -qq
+apt-get install -y -qq build-essential cmake git python3 python3-pip libcurl4-openssl-dev ccache
+pip install -q -U "huggingface_hub[cli]" hf_transfer
+export HF_HUB_ENABLE_HF_TRANSFER=1          # fast download
+# the HF CLI in hf_hub 2.x is `hf`, NOT `huggingface-cli`
+
+cd /root && git clone --depth 1 https://github.com/ggml-org/llama.cpp && cd llama.cpp
+# Blackwell PRO 6000 -> 120 ; Ampere A6000 -> 86
+cmake -B build -DGGML_CUDA=ON -DCMAKE_CUDA_ARCHITECTURES=120 -DLLAMA_CURL=ON -DGGML_CCACHE=ON
+cmake --build build --config Release -j"$(nproc)" --target llama-server
+```
+
+### 2) Download the model
+```bash
+# Config A — Q8 + MTP
+hf download nesilabs/Nesi2 --include "Nesi2-Q8_0.gguf" "Nesi2-mtp-Q8_0.gguf" --local-dir /root/models/nesi2
+# Config B — Q6_K
+hf download nesilabs/Nesi2 --include "Nesi2-Q6_K*.gguf" --local-dir /root/models/nesi2
+```
+
+### 3) Launch `llama-server` in tmux
+Never start it with `setsid`/`nohup` over SSH (they die when the pipe closes).
+Use **tmux** so it survives the SSH session.
+
+#### Config A — Q8_0 + MTP, 5 users @ 240k (production, RTX PRO 6000 WS)
+`--parallel N` splits `--ctx-size` across slots → `n_ctx_slot = ctx_size / parallel`.
+For **5 slots of 240k each** you need `--ctx-size 1228800` (= 5 × 245760), a
+**quantized KV cache** (`q8_0`), and the MTP draft:
+```bash
+tmux new-session -d -s nesi2 "/root/llama.cpp/build/bin/llama-server \
+  --model /root/models/nesi2/Nesi2-Q8_0.gguf --alias nesi2 \
+  --n-gpu-layers 999 -fa on \
+  --cache-type-k q8_0 --cache-type-v q8_0 \
+  --spec-type draft-mtp --model-draft /root/models/nesi2/Nesi2-mtp-Q8_0.gguf --spec-draft-n-max 3 \
+  --ctx-size 1228800 --parallel 5 \
+  --host 0.0.0.0 --port 8080 --api-key <YOUR_API_KEY> \
+  > /root/llama.log 2>&1"
+```
+VRAM ≈ 84 / 96 GB. Drop `--spec-type/--model-draft` if your build lacks MTP.
+
+#### Config B — Q6_K, single power user @ 240k
+```bash
+tmux new-session -d -s nesi2 "/root/llama.cpp/build/bin/llama-server \
+  --model /root/models/nesi2/Nesi2-Q6_K.gguf --alias nesi2 \
+  --ctx-size 245760 --parallel 1 --n-gpu-layers 999 -fa on \
+  --host 0.0.0.0 --port 8080 --api-key <YOUR_API_KEY> \
+  > /root/llama.log 2>&1"
+```
+For **3 users @ 240k each** on a 96 GB card, use `--ctx-size 737280 --parallel 3`
+plus `--cache-type-k q8_0 --cache-type-v q8_0`. If it OOMs, drop to
+`q4_0` KV, lower per-user context (e.g. `--ctx-size 393216 --parallel 3` = 128k
+each), or move to a 2× GPU box. Under `--parallel 3` per-stream speed drops
+(~55 → ~20–30 tok/s) but aggregate throughput goes up.
+
+Wait for load (VRAM up + `server is listening`):
+```bash
+grep -m1 "server is listening" <(tail -f /root/llama.log)
+```
+
+### 4) Point the gateway (LiteLLM) at the box
+The box's **public IP and 8080 port change on every (re)start**, so this is the
+only step you repeat. On the LiteLLM host:
+```bash
+# .env
+NESI2_API_BASE=http://<BOX_PUBLIC_IP>:<BOX_8080_HOSTPORT>/v1
+NESI2_API_KEY=<YOUR_API_KEY>
+# then
+docker compose up -d litellm
+```
+
+### 5) Verify end-to-end
+```bash
+curl -s -X POST https://<your-gateway>/v1/chat/completions \
+  -H "Authorization: Bearer <client_key>" -H "Content-Type: application/json" \
+  -d '{"model":"nesi2","messages":[{"role":"user","content":"di OK"}],"max_tokens":5}'
+```
+
+---
+
+## Lessons learned & recommendations
+
+- **`--parallel 1` is mandatory to actually get the full 240k in one slot.** The
+  llama.cpp default (`--parallel 4`) silently gives each slot `ctx/4`.
+- **`-fa on` (flash-attention)** — keep it on; large context is unusable without it.
+- **tmux, not setsid/nohup.** Over SSH the detached process dies and you get an
+  empty log; tmux survives.
+- **Agent discipline > raw capability.** As an agent Nesi2 shines because of
+  *tool-calling discipline*: it acts (one concrete tool call per turn) instead of
+  narrating. Give it a lean system prompt that says: act don't narrate; write your
+  own Python for anything past a simple HTTP request (WebSocket, sockets, rotating
+  CSRF); get code-exec first and confirm with `id`; and **keep durable state on
+  disk** (a `NOTES.md` + reusable scripts) so a context compaction doesn't make it
+  re-derive what it already solved.
+- **Isolate the agent's filesystem for honest evals.** A harness whose shell can
+  read your machine will "solve" a CTF by reading the solution/writeups off disk
+  instead of attacking live. Deny reads outside the target (regex guard in the tool
+  layer, or run the agent under `sandbox-exec`/a container). Network to the target
+  stays open.
+- **KV quantization scales users cheaply.** `--cache-type-k/v q8_0` roughly doubles
+  how many 240k slots fit, with no quality drift we could measure; it's what makes
+  the multi-user profiles fit a single 96 GB card.
+- **Max-Q vs WS.** The power-capped Max-Q PRO 6000 is ~2.5× slower than the full WS
+  for ~0.25 $/h less. For interactive/agent use pay for the WS; for cheap batch,
+  Max-Q is fine.
+- **Speculative decode (MTP).** The `*-mtp*.gguf` draft head is included; under
+  concurrency it did **not** help throughput in our tests, so we run without it for
+  multi-user serving and keep it available for single-stream latency.
+
+## ⚠️ Legal Notice / Disclaimer
+
+**Nesi2 is intended EXCLUSIVELY for security professionals, for lawful and
+authorized activities.**
+
+- **Authorization required.** Use it only against systems, networks, or
+  applications for which you have **explicit written permission** (a contracted
+  penetration test, an in-scope bug bounty program, or your own/lab environments).
+  Using it against systems without authorization is **illegal** and strictly
+  prohibited.
+- **User responsibility.** You are the **sole responsible party** for how you use
+  this model and for complying with all applicable laws in your jurisdiction
+  (including computer-misuse, data-protection/GDPR, and intellectual-property laws).
+- **No warranty.** The model is provided "as is", **without warranty** of accuracy,
+  fitness, or results. It may produce incorrect information — always verify before acting.
+- **Limitation of liability.** Nesilabs is **not liable** for any damages, losses,
+  or legal consequences arising from the use or misuse of this model, including any
+  unauthorized or unlawful use.
+- **Prohibited use.** Using Nesi2 for illegal activities, unauthorized access,
+  extortion, harm to third parties, or any purpose that violates the law or these
+  terms is prohibited.
+
+By using Nesi2 you accept this notice and the Nesilabs Terms of Service and
+Acceptable Use Policy.
+
+## License
+Released under **Apache 2.0**. Packaged and optimized by Nesilabs.

chat_template.jinja

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+{%- set video_count = namespace(value=0) %}
+{%- macro render_content(content, do_vision_count, is_system_content=false) %}
+    {%- if content is string %}
+        {{- content }}
+    {%- elif content is iterable and content is not mapping %}
+        {%- for item in content %}
+            {%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
+                {%- if is_system_content %}
+                    {{- raise_exception('System message cannot contain images.') }}
+                {%- endif %}
+                {%- if do_vision_count %}
+                    {%- set image_count.value = image_count.value + 1 %}
+                {%- endif %}
+                {%- if add_vision_id %}
+                    {{- 'Picture ' ~ image_count.value ~ ': ' }}
+                {%- endif %}
+                {{- '<|vision_start|><|image_pad|><|vision_end|>' }}
+            {%- elif 'video' in item or item.type == 'video' %}
+                {%- if is_system_content %}
+                    {{- raise_exception('System message cannot contain videos.') }}
+                {%- endif %}
+                {%- if do_vision_count %}
+                    {%- set video_count.value = video_count.value + 1 %}
+                {%- endif %}
+                {%- if add_vision_id %}
+                    {{- 'Video ' ~ video_count.value ~ ': ' }}
+                {%- endif %}
+                {{- '<|vision_start|><|video_pad|><|vision_end|>' }}
+            {%- elif 'text' in item %}
+                {{- item.text }}
+            {%- else %}
+                {{- raise_exception('Unexpected item type in content.') }}
+            {%- endif %}
+        {%- endfor %}
+    {%- elif content is none or content is undefined %}
+        {{- '' }}
+    {%- else %}
+        {{- raise_exception('Unexpected content type.') }}
+    {%- endif %}
+{%- endmacro %}
+{%- if not messages %}
+    {{- raise_exception('No messages provided.') }}
+{%- endif %}
+{%- set reasoning_instructions = '' %}
+{%- if enable_thinking is undefined or enable_thinking is true %}
+    {%- set resolved_reasoning_effort = reasoning_effort|default('xhigh') %}
+    {%- if resolved_reasoning_effort not in ('xhigh', 'medium', 'low') %}
+        {{- raise_exception('Unexpected reasoning effort ' ~ reasoning_effort ~ '. Supported types are xhigh (default), medium, and low.') }}
+    {%- endif %}
+    {%- if resolved_reasoning_effort == 'xhigh' %}
+        {%- set reasoning_instructions = 'Reasoning effort is set to xhigh. Please think carefully through the task, validate key assumptions, consider plausible alternatives, and prioritize correctness, consistency, and clarity in the final answer.' %}
+    {%- elif resolved_reasoning_effort == 'low' %}
+        {%- set reasoning_instructions = 'Reasoning effort is set to low. Keep your thinking brief and focused, moving directly to the conclusion without unnecessary elaboration.' %}
+    {%- endif %}
+{%- endif %}
+{%- if tools and tools is iterable and tools is not mapping %}
+    {{- '<|im_start|>system\n' }}
+    {%- if reasoning_instructions %}
+        {{- reasoning_instructions + '\n\n' }}
+    {%- endif %}
+    {{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>" }}
+    {{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
+    {%- if messages[0].role == 'system' %}
+        {%- set content = render_content(messages[0].content, false, true)|trim %}
+        {%- if content %}
+            {{- '\n\n' + content }}
+        {%- endif %}
+    {%- endif %}
+    {{- '<|im_end|>\n' }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {%- set content = render_content(messages[0].content, false, true)|trim %}
+        {%- if content %}
+            {{- '<|im_start|>system\n' + (reasoning_instructions + '\n\n' if reasoning_instructions else '')  + content + '<|im_end|>\n' }}
+        {%- elif reasoning_instructions %}
+            {{- '<|im_start|>system\n' + reasoning_instructions + '<|im_end|>\n' }}
+        {%- endif %}
+    {%- elif reasoning_instructions %}
+        {{- '<|im_start|>system\n' + reasoning_instructions + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" %}
+        {%- set content = render_content(message.content, false)|trim %}
+        {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
+            {%- set ns.multi_step_tool = false %}
+            {%- set ns.last_query_index = index %}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if ns.multi_step_tool %}
+    {{- raise_exception('No user query found in messages.') }}
+{%- endif %}
+{%- for message in messages %}
+    {%- set content = render_content(message.content, true)|trim %}
+    {%- if message.role == "system" %}
+        {%- if not loop.first %}
+            {{- raise_exception('System message must be at the beginning.') }}
+        {%- endif %}
+    {%- elif message.role == "user" %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- endif %}
+        {%- set reasoning_content = reasoning_content|trim %}
+        {%- if preserve_thinking is undefined or preserve_thinking is true or loop.index0 > ns.last_query_index %}
+            {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if tool_call.function is defined %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {%- if loop.first %}
+                    {%- if content|trim %}
+                        {{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                    {%- else %}
+                        {{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                    {%- endif %}
+                {%- else %}
+                    {{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                {%- endif %}
+                {%- if tool_call.arguments is defined and tool_call.arguments != '' %}
+                    {%- for args_name, args_value in tool_call.arguments|items %}
+                        {{- '<parameter=' + args_name + '>\n' }}
+                        {%- set args_value = args_value | string if args_value is string else args_value | tojson | safe %}
+                        {{- args_value }}
+                        {{- '\n</parameter>\n' }}
+                    {%- endfor %}
+                {%- endif %}
+                {{- '</function>\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.previtem and loop.previtem.role != "tool" %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if not loop.last and loop.nextitem.role != "tool" %}
+            {{- '<|im_end|>\n' }}
+        {%- elif loop.last %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- else %}
+        {{- raise_exception('Unexpected message role.') }}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- else %}
+        {{- '<think>\n' }}
+    {%- endif %}
+{%- endif %}

config.json

@@ -0,0 +1,145 @@
+{
+  "architectures": [
+    "Qwen3_5ForConditionalGeneration"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "dtype": "bfloat16",
+  "image_token_id": 248056,
+  "language_model_only": false,
+  "model_type": "qwen3_5",
+  "pad_token_id": 0,
+  "text_config": {
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "attn_output_gate": true,
+    "bos_token_id": 248044,
+    "dtype": "bfloat16",
+    "eos_token_id": 248044,
+    "full_attention_interval": 4,
+    "head_dim": 256,
+    "hidden_act": "silu",
+    "hidden_size": 5120,
+    "initializer_range": 0.02,
+    "intermediate_size": 17408,
+    "layer_types": [
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention"
+    ],
+    "linear_conv_kernel_dim": 4,
+    "linear_key_head_dim": 128,
+    "linear_num_key_heads": 16,
+    "linear_num_value_heads": 48,
+    "linear_value_head_dim": 128,
+    "mamba_ssm_dtype": "float32",
+    "max_position_embeddings": 262144,
+    "model_type": "qwen3_5_text",
+    "mtp_num_hidden_layers": 1,
+    "mtp_use_dedicated_embeddings": false,
+    "num_attention_heads": 24,
+    "num_hidden_layers": 64,
+    "num_key_value_heads": 4,
+    "output_gate_type": "swish",
+    "pad_token_id": null,
+    "partial_rotary_factor": 0.25,
+    "rms_norm_eps": 1e-06,
+    "rope_parameters": {
+      "mrope_interleaved": true,
+      "mrope_section": [
+        11,
+        11,
+        10
+      ],
+      "partial_rotary_factor": 0.25,
+      "rope_theta": 10000000,
+      "rope_type": "default"
+    },
+    "tie_word_embeddings": false,
+    "use_cache": true,
+    "vocab_size": 248320
+  },
+  "tie_word_embeddings": false,
+  "transformers_version": "5.14.1",
+  "video_token_id": 248057,
+  "vision_config": {
+    "deepstack_visual_indexes": [],
+    "depth": 27,
+    "dtype": "bfloat16",
+    "hidden_act": "gelu_pytorch_tanh",
+    "hidden_size": 1152,
+    "in_channels": 3,
+    "initializer_range": 0.02,
+    "intermediate_size": 4304,
+    "model_type": "qwen3_5_vision",
+    "num_heads": 16,
+    "num_position_embeddings": 2304,
+    "out_hidden_size": 5120,
+    "patch_size": 16,
+    "spatial_merge_size": 2,
+    "temporal_patch_size": 2
+  },
+  "vision_end_token_id": 248054,
+  "vision_start_token_id": 248053
+}

generation_config.json

@@ -0,0 +1,13 @@
+{
+  "bos_token_id": 248044,
+  "do_sample": true,
+  "eos_token_id": [
+    248046,
+    248044
+  ],
+  "pad_token_id": 248044,
+  "temperature": 1.0,
+  "top_k": 20,
+  "top_p": 0.95,
+  "transformers_version": "5.14.1"
+}

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model-auxiliary.safetensors

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+size 849400392

preprocessor_config.json

@@ -0,0 +1,21 @@
+{
+    "size": {
+        "longest_edge": 16777216,
+        "shortest_edge": 65536
+    },
+    "patch_size": 16,
+    "temporal_patch_size": 2,
+    "merge_size": 2,
+    "image_mean": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "image_std": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "processor_class": "Qwen3VLProcessor",
+    "image_processor_type": "Qwen2VLImageProcessorFast"
+}

tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6f32ce20dc35f57a7f9ad1eac03525bd7d30f9df8cea6507e958279cc3657706
+size 19989492

tokenizer_config.json

@@ -0,0 +1,32 @@
+{
+  "add_prefix_space": false,
+  "audio_bos_token": "<|audio_start|>",
+  "audio_eos_token": "<|audio_end|>",
+  "audio_token": "<|audio_pad|>",
+  "backend": "tokenizers",
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "image_token": "<|image_pad|>",
+  "is_local": false,
+  "local_files_only": false,
+  "model_max_length": 262144,
+  "model_specific_special_tokens": {
+    "audio_bos_token": "<|audio_start|>",
+    "audio_eos_token": "<|audio_end|>",
+    "audio_token": "<|audio_pad|>",
+    "image_token": "<|image_pad|>",
+    "video_token": "<|video_pad|>",
+    "vision_bos_token": "<|vision_start|>",
+    "vision_eos_token": "<|vision_end|>"
+  },
+  "pad_token": "<|endoftext|>",
+  "pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null,
+  "video_token": "<|video_pad|>",
+  "vision_bos_token": "<|vision_start|>",
+  "vision_eos_token": "<|vision_end|>"
+}

video_preprocessor_config.json

@@ -0,0 +1,21 @@
+{
+    "size": {
+        "longest_edge": 25165824,
+        "shortest_edge": 4096
+    },
+    "patch_size": 16,
+    "temporal_patch_size": 2,
+    "merge_size": 2,
+    "image_mean": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "image_std": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "processor_class": "Qwen3VLProcessor",
+    "video_processor_type": "Qwen3VLVideoProcessor"
+}