Instructions to use tensorblock/Arch-Function-3B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tensorblock/Arch-Function-3B-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="tensorblock/Arch-Function-3B-GGUF") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tensorblock/Arch-Function-3B-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use tensorblock/Arch-Function-3B-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf tensorblock/Arch-Function-3B-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/Arch-Function-3B-GGUF:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tensorblock/Arch-Function-3B-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/Arch-Function-3B-GGUF:Q2_K
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf tensorblock/Arch-Function-3B-GGUF:Q2_K # Run inference directly in the terminal: ./llama-cli -hf tensorblock/Arch-Function-3B-GGUF:Q2_K
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf tensorblock/Arch-Function-3B-GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf tensorblock/Arch-Function-3B-GGUF:Q2_K
Use Docker
docker model run hf.co/tensorblock/Arch-Function-3B-GGUF:Q2_K
- LM Studio
- Jan
- vLLM
How to use tensorblock/Arch-Function-3B-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "tensorblock/Arch-Function-3B-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tensorblock/Arch-Function-3B-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/tensorblock/Arch-Function-3B-GGUF:Q2_K
- SGLang
How to use tensorblock/Arch-Function-3B-GGUF with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "tensorblock/Arch-Function-3B-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tensorblock/Arch-Function-3B-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "tensorblock/Arch-Function-3B-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tensorblock/Arch-Function-3B-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use tensorblock/Arch-Function-3B-GGUF with Ollama:
ollama run hf.co/tensorblock/Arch-Function-3B-GGUF:Q2_K
- Unsloth Desktop
- Pi
How to use tensorblock/Arch-Function-3B-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf tensorblock/Arch-Function-3B-GGUF:Q2_K
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "tensorblock/Arch-Function-3B-GGUF:Q2_K" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use tensorblock/Arch-Function-3B-GGUF with Docker Model Runner:
docker model run hf.co/tensorblock/Arch-Function-3B-GGUF:Q2_K
- Lemonade
How to use tensorblock/Arch-Function-3B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tensorblock/Arch-Function-3B-GGUF:Q2_K
Run and chat with the model
lemonade run user.Arch-Function-3B-GGUF-Q2_K
List all available models
lemonade list
- Hermes Agent
How to use tensorblock/Arch-Function-3B-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf tensorblock/Arch-Function-3B-GGUF:Q2_K
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default tensorblock/Arch-Function-3B-GGUF:Q2_K
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use tensorblock/Arch-Function-3B-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf tensorblock/Arch-Function-3B-GGUF:Q2_K
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "tensorblock/Arch-Function-3B-GGUF:Q2_K" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Upload folder using huggingface_hub
Browse files- .gitattributes +12 -0
- Arch-Function-3B-Q2_K.gguf +3 -0
- Arch-Function-3B-Q3_K_L.gguf +3 -0
- Arch-Function-3B-Q3_K_M.gguf +3 -0
- Arch-Function-3B-Q3_K_S.gguf +3 -0
- Arch-Function-3B-Q4_0.gguf +3 -0
- Arch-Function-3B-Q4_K_M.gguf +3 -0
- Arch-Function-3B-Q4_K_S.gguf +3 -0
- Arch-Function-3B-Q5_0.gguf +3 -0
- Arch-Function-3B-Q5_K_M.gguf +3 -0
- Arch-Function-3B-Q5_K_S.gguf +3 -0
- Arch-Function-3B-Q6_K.gguf +3 -0
- Arch-Function-3B-Q8_0.gguf +3 -0
- README.md +86 -0
.gitattributes
CHANGED
|
@@ -33,3 +33,15 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
+
Arch-Function-3B-Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
|
| 37 |
+
Arch-Function-3B-Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
|
| 38 |
+
Arch-Function-3B-Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
|
| 39 |
+
Arch-Function-3B-Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
|
| 40 |
+
Arch-Function-3B-Q4_0.gguf filter=lfs diff=lfs merge=lfs -text
|
| 41 |
+
Arch-Function-3B-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
|
| 42 |
+
Arch-Function-3B-Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
|
| 43 |
+
Arch-Function-3B-Q5_0.gguf filter=lfs diff=lfs merge=lfs -text
|
| 44 |
+
Arch-Function-3B-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
|
| 45 |
+
Arch-Function-3B-Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
|
| 46 |
+
Arch-Function-3B-Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
|
| 47 |
+
Arch-Function-3B-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
|
Arch-Function-3B-Q2_K.gguf
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9b8001d35c689c75392ce36dda44a4bb6b47a693b727c1616bc1283fba8467ad
|
| 3 |
+
size 1274756064
|
Arch-Function-3B-Q3_K_L.gguf
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0334ddadca03810d7ed3566c5c0cb24cd68e05c96276833971140cce5a035048
|
| 3 |
+
size 1707391968
|
Arch-Function-3B-Q3_K_M.gguf
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e52913327e685e2e9a919ff453a92d30376a3000cb3c31745fd7bc286db3912e
|
| 3 |
+
size 1590475744
|
Arch-Function-3B-Q3_K_S.gguf
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:93d3c26d03cd4bfeeb1b52a9899dcb11704c49bc4ff573a8b3cdaa652d4a623e
|
| 3 |
+
size 1454357472
|
Arch-Function-3B-Q4_0.gguf
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:2bc45764476c7c86c42b91cb74196f428cc9216c55f7f796774798da64315043
|
| 3 |
+
size 1822850016
|
Arch-Function-3B-Q4_K_M.gguf
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b339eadcab85b9a2a5718efc9de4b18bba0e526b5157d9971e22554617612cda
|
| 3 |
+
size 1929903072
|
Arch-Function-3B-Q4_K_S.gguf
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:76ff2ae8f02e29ef637b0af5b95695fa4d7e83a96dadfd971bfa79c16da6ff2f
|
| 3 |
+
size 1834384352
|
Arch-Function-3B-Q5_0.gguf
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:8f901c7d841f531dbbaaf845193c1743b9cdf8cf3e6667353e44d6c513c877e3
|
| 3 |
+
size 2169666528
|
Arch-Function-3B-Q5_K_M.gguf
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:de0811917476e3a254434f02ae720cb786131b254dd1f3cb95139c26af59a52b
|
| 3 |
+
size 2224815072
|
Arch-Function-3B-Q5_K_S.gguf
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:21caba21c12523df8791ef5e60607263b849109b5199189a9e6c1f4574ab5e22
|
| 3 |
+
size 2169666528
|
Arch-Function-3B-Q6_K.gguf
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b0ce0434a322ba5cc1b8d4b9a98e9324f709eab50771df59ea8537caa881fd09
|
| 3 |
+
size 2538159072
|
Arch-Function-3B-Q8_0.gguf
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:25e5ffaafa29d151edf4f54e94b23246a9c5409a99ed53a3d62fe64f7abb743c
|
| 3 |
+
size 3285476320
|
README.md
ADDED
|
@@ -0,0 +1,86 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: other
|
| 3 |
+
license_name: katanemo-research
|
| 4 |
+
license_link: https://huggingface.co/katanemolabs/Arch-Function-1.5B/blob/main/LICENSE
|
| 5 |
+
base_model: katanemo/Arch-Function-3B
|
| 6 |
+
language:
|
| 7 |
+
- en
|
| 8 |
+
pipeline_tag: text-generation
|
| 9 |
+
library_name: transformers
|
| 10 |
+
tags:
|
| 11 |
+
- TensorBlock
|
| 12 |
+
- GGUF
|
| 13 |
+
---
|
| 14 |
+
|
| 15 |
+
<div style="width: auto; margin-left: auto; margin-right: auto">
|
| 16 |
+
<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
|
| 17 |
+
</div>
|
| 18 |
+
<div style="display: flex; justify-content: space-between; width: 100%;">
|
| 19 |
+
<div style="display: flex; flex-direction: column; align-items: flex-start;">
|
| 20 |
+
<p style="margin-top: 0.5em; margin-bottom: 0em;">
|
| 21 |
+
Feedback and support: TensorBlock's <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a>
|
| 22 |
+
</p>
|
| 23 |
+
</div>
|
| 24 |
+
</div>
|
| 25 |
+
|
| 26 |
+
## katanemo/Arch-Function-3B - GGUF
|
| 27 |
+
|
| 28 |
+
This repo contains GGUF format model files for [katanemo/Arch-Function-3B](https://huggingface.co/katanemo/Arch-Function-3B).
|
| 29 |
+
|
| 30 |
+
The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
|
| 31 |
+
|
| 32 |
+
<div style="text-align: left; margin: 20px 0;">
|
| 33 |
+
<a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
|
| 34 |
+
Run them on the TensorBlock client using your local machine ↗
|
| 35 |
+
</a>
|
| 36 |
+
</div>
|
| 37 |
+
|
| 38 |
+
## Prompt template
|
| 39 |
+
|
| 40 |
+
```
|
| 41 |
+
<|im_start|>system
|
| 42 |
+
{system_prompt}<|im_end|>
|
| 43 |
+
<|im_start|>user
|
| 44 |
+
{prompt}<|im_end|>
|
| 45 |
+
<|im_start|>assistant
|
| 46 |
+
```
|
| 47 |
+
|
| 48 |
+
## Model file specification
|
| 49 |
+
|
| 50 |
+
| Filename | Quant type | File Size | Description |
|
| 51 |
+
| -------- | ---------- | --------- | ----------- |
|
| 52 |
+
| [Arch-Function-3B-Q2_K.gguf](https://huggingface.co/tensorblock/Arch-Function-3B-GGUF/blob/main/Arch-Function-3B-Q2_K.gguf) | Q2_K | 1.275 GB | smallest, significant quality loss - not recommended for most purposes |
|
| 53 |
+
| [Arch-Function-3B-Q3_K_S.gguf](https://huggingface.co/tensorblock/Arch-Function-3B-GGUF/blob/main/Arch-Function-3B-Q3_K_S.gguf) | Q3_K_S | 1.454 GB | very small, high quality loss |
|
| 54 |
+
| [Arch-Function-3B-Q3_K_M.gguf](https://huggingface.co/tensorblock/Arch-Function-3B-GGUF/blob/main/Arch-Function-3B-Q3_K_M.gguf) | Q3_K_M | 1.590 GB | very small, high quality loss |
|
| 55 |
+
| [Arch-Function-3B-Q3_K_L.gguf](https://huggingface.co/tensorblock/Arch-Function-3B-GGUF/blob/main/Arch-Function-3B-Q3_K_L.gguf) | Q3_K_L | 1.707 GB | small, substantial quality loss |
|
| 56 |
+
| [Arch-Function-3B-Q4_0.gguf](https://huggingface.co/tensorblock/Arch-Function-3B-GGUF/blob/main/Arch-Function-3B-Q4_0.gguf) | Q4_0 | 1.823 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
|
| 57 |
+
| [Arch-Function-3B-Q4_K_S.gguf](https://huggingface.co/tensorblock/Arch-Function-3B-GGUF/blob/main/Arch-Function-3B-Q4_K_S.gguf) | Q4_K_S | 1.834 GB | small, greater quality loss |
|
| 58 |
+
| [Arch-Function-3B-Q4_K_M.gguf](https://huggingface.co/tensorblock/Arch-Function-3B-GGUF/blob/main/Arch-Function-3B-Q4_K_M.gguf) | Q4_K_M | 1.930 GB | medium, balanced quality - recommended |
|
| 59 |
+
| [Arch-Function-3B-Q5_0.gguf](https://huggingface.co/tensorblock/Arch-Function-3B-GGUF/blob/main/Arch-Function-3B-Q5_0.gguf) | Q5_0 | 2.170 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
|
| 60 |
+
| [Arch-Function-3B-Q5_K_S.gguf](https://huggingface.co/tensorblock/Arch-Function-3B-GGUF/blob/main/Arch-Function-3B-Q5_K_S.gguf) | Q5_K_S | 2.170 GB | large, low quality loss - recommended |
|
| 61 |
+
| [Arch-Function-3B-Q5_K_M.gguf](https://huggingface.co/tensorblock/Arch-Function-3B-GGUF/blob/main/Arch-Function-3B-Q5_K_M.gguf) | Q5_K_M | 2.225 GB | large, very low quality loss - recommended |
|
| 62 |
+
| [Arch-Function-3B-Q6_K.gguf](https://huggingface.co/tensorblock/Arch-Function-3B-GGUF/blob/main/Arch-Function-3B-Q6_K.gguf) | Q6_K | 2.538 GB | very large, extremely low quality loss |
|
| 63 |
+
| [Arch-Function-3B-Q8_0.gguf](https://huggingface.co/tensorblock/Arch-Function-3B-GGUF/blob/main/Arch-Function-3B-Q8_0.gguf) | Q8_0 | 3.285 GB | very large, extremely low quality loss - not recommended |
|
| 64 |
+
|
| 65 |
+
|
| 66 |
+
## Downloading instruction
|
| 67 |
+
|
| 68 |
+
### Command line
|
| 69 |
+
|
| 70 |
+
Firstly, install Huggingface Client
|
| 71 |
+
|
| 72 |
+
```shell
|
| 73 |
+
pip install -U "huggingface_hub[cli]"
|
| 74 |
+
```
|
| 75 |
+
|
| 76 |
+
Then, downoad the individual model file the a local directory
|
| 77 |
+
|
| 78 |
+
```shell
|
| 79 |
+
huggingface-cli download tensorblock/Arch-Function-3B-GGUF --include "Arch-Function-3B-Q2_K.gguf" --local-dir MY_LOCAL_DIR
|
| 80 |
+
```
|
| 81 |
+
|
| 82 |
+
If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
|
| 83 |
+
|
| 84 |
+
```shell
|
| 85 |
+
huggingface-cli download tensorblock/Arch-Function-3B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
|
| 86 |
+
```
|