Instructions to use zerolimites/Qwen3-0.6B-Base-Normal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use zerolimites/Qwen3-0.6B-Base-Normal 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 zerolimites/Qwen3-0.6B-Base-Normal:F16 # Run inference directly in the terminal: llama cli -hf zerolimites/Qwen3-0.6B-Base-Normal:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf zerolimites/Qwen3-0.6B-Base-Normal:F16 # Run inference directly in the terminal: llama cli -hf zerolimites/Qwen3-0.6B-Base-Normal:F16
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf zerolimites/Qwen3-0.6B-Base-Normal:F16 # Run inference directly in the terminal: ./build/bin/llama cli -hf zerolimites/Qwen3-0.6B-Base-Normal:F16
Use Docker
docker model run hf.co/zerolimites/Qwen3-0.6B-Base-Normal:F16
- Llama new
- LM Studio
- Jan
- vLLM
How to use zerolimites/Qwen3-0.6B-Base-Normal with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "zerolimites/Qwen3-0.6B-Base-Normal" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "zerolimites/Qwen3-0.6B-Base-Normal", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/zerolimites/Qwen3-0.6B-Base-Normal:F16
- Ollama
How to use zerolimites/Qwen3-0.6B-Base-Normal with Ollama:
ollama run hf.co/zerolimites/Qwen3-0.6B-Base-Normal:F16
- Unsloth Desktop
- Pi
How to use zerolimites/Qwen3-0.6B-Base-Normal with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf zerolimites/Qwen3-0.6B-Base-Normal:F16
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": "zerolimites/Qwen3-0.6B-Base-Normal:F16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use zerolimites/Qwen3-0.6B-Base-Normal with Docker Model Runner:
docker model run hf.co/zerolimites/Qwen3-0.6B-Base-Normal:F16
- Lemonade
How to use zerolimites/Qwen3-0.6B-Base-Normal with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull zerolimites/Qwen3-0.6B-Base-Normal:F16
Run and chat with the model
lemonade run user.Qwen3-0.6B-Base-Normal-F16
List all available models
lemonade list
- Hermes Agent
How to use zerolimites/Qwen3-0.6B-Base-Normal with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf zerolimites/Qwen3-0.6B-Base-Normal:F16
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 zerolimites/Qwen3-0.6B-Base-Normal:F16
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use zerolimites/Qwen3-0.6B-Base-Normal with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf zerolimites/Qwen3-0.6B-Base-Normal:F16
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 "zerolimites/Qwen3-0.6B-Base-Normal:F16" \ --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"
Download code_baseline_results.json from zerolimites/Qwen3-0.6B-Base-Normal: direct link, hf CLI and curl.
- Browser
- Download file 16.9 kB
-
https://huggingface.co/zerolimites/Qwen3-0.6B-Base-Normal/resolve/main/code_baseline_results.json
- Command line
-
hf download hf://zerolimites/Qwen3-0.6B-Base-Normal/code_baseline_results.json
-
curl -L -o code_baseline_results.json https://huggingface.co/zerolimites/Qwen3-0.6B-Base-Normal/resolve/main/code_baseline_results.json
16.9 kB
| { | |
| "total": 28, | |
| "passed": 13, | |
| "accuracy": 46.43, | |
| "avg_tokens": 45.4, | |
| "elapsed_sec": 111.79, | |
| "results": [ | |
| { | |
| "id": "PY_01", | |
| "category": "Python", | |
| "prompt": "Write a Python function `def merge_intervals(intervals: list[list[int]]) -> list[list[int]]:` that merges all overlapping `[start, end]` intervals and returns the sorted merged list. Return only the code.", | |
| "passed": false, | |
| "detail": "IndentationError: expected an indented block after 'if' statement on line 13", | |
| "num_tokens": 90, | |
| "response": "```python\ndef merge_intervals(intervals: list[list[int]]) -> list[list[int]]:\n if not intervals:\n return []\n \n # Sort intervals by start time\n intervals.sort(key=lambda x: x[0])\n \n result = [intervals[0]]\n for start, end in intervals[1:]:\n last_start, last_end = result[-1]\n if start <= last_end:\n # Overlapping intervals," | |
| }, | |
| { | |
| "id": "PY_02", | |
| "category": "Python", | |
| "prompt": "Write a Python function `def flatten_list(nested: list) -> list:` that recursively flattens an arbitrarily nested list of integers into a single 1D list. Return only the code.", | |
| "passed": true, | |
| "detail": "Passed all assertions", | |
| "num_tokens": 52, | |
| "response": "```python\ndef flatten_list(nested: list) -> list:\n result = []\n for item in nested:\n if isinstance(item, list):\n result.extend(flatten_list(item))\n else:\n result.append(item)\n return result\n```" | |
| }, | |
| { | |
| "id": "PY_03", | |
| "category": "Python", | |
| "prompt": "Write a Python function `def first_unique_char(s: str) -> int:` that returns the 0-based index of the first non-repeating character in string `s`, or `-1` if none exists. Return only the code.", | |
| "passed": false, | |
| "detail": "IndentationError: expected an indented block after 'for' statement on line 16", | |
| "num_tokens": 90, | |
| "response": "```python\ndef first_unique_char(s: str) -> int:\n if not s:\n return -1\n\n # Count the frequency of each character\n freq = {}\n for char in s:\n if char in freq:\n freq[char] += 1\n else:\n freq[char] = 1\n\n # Find the first character with a frequency of 1\n for index, char in enumerate(s):" | |
| }, | |
| { | |
| "id": "PY_04", | |
| "category": "Python", | |
| "prompt": "Write a Python function `def group_anagrams(words: list[str]) -> list[list[str]]:` that groups anagrams together. Return only the code.", | |
| "passed": false, | |
| "detail": "AssertionError", | |
| "num_tokens": 85, | |
| "response": "```python\ndef group_anagrams(words: list[str]) -> list[list[str]]:\n result = []\n for word in words:\n if not word:\n continue\n if len(word) == 1:\n result.append([word])\n else:\n # Sort the characters to form a unique key\n sorted_word = ''.join(sorted(word))\n result.append([sorted_word])\n return result\n```" | |
| }, | |
| { | |
| "id": "PY_05", | |
| "category": "Python", | |
| "prompt": "Write a Python function `def is_valid_brackets(s: str) -> bool:` that checks if a string containing only `'()[]{}'` has valid matching and properly nested brackets. Return only the code.", | |
| "passed": false, | |
| "detail": "AssertionError", | |
| "num_tokens": 78, | |
| "response": "```python\ndef is_valid_brackets(s: str) -> bool:\n stack = []\n for char in s:\n if char in '([{':\n stack.append(char)\n elif char in ')]}':\n if not stack or stack[-1] != char:\n return False\n else:\n return False\n return len(stack) == 0\n```" | |
| }, | |
| { | |
| "id": "PY_06", | |
| "category": "Python", | |
| "prompt": "Write a Python function `def longest_common_prefix(strs: list[str]) -> str:` that finds the longest common prefix string amongst an array of strings (or `\"\"` if none). Return only the code.", | |
| "passed": false, | |
| "detail": "AssertionError", | |
| "num_tokens": 31, | |
| "response": "```python\ndef longest_common_prefix(strs: list[str]) -> str:\n if not strs:\n return \"\"\n return strs[0]\n```" | |
| }, | |
| { | |
| "id": "PY_07", | |
| "category": "Python", | |
| "prompt": "Write a Python function `def rotate_right(nums: list[int], k: int) -> list[int]:` that returns a new list with the elements of `nums` rotated to the right by `k` steps (where `k` can be larger than `len(nums)`). Return only the code.", | |
| "passed": false, | |
| "detail": "AssertionError", | |
| "num_tokens": 62, | |
| "response": "```python\ndef rotate_right(nums: list[int], k: int) -> list[int]:\n # If k is larger than the length of nums, rotate the list by k steps\n if k > len(nums):\n k %= len(nums)\n return nums[k:] + nums[:k]\n```" | |
| }, | |
| { | |
| "id": "LINUX_01", | |
| "category": "Linux Commands", | |
| "prompt": "Write a single Linux bash command to replace all occurrences of `DEBUG` with `ERROR` in `app.conf` and write the output to `app_prod.conf`. Return only the command.", | |
| "passed": true, | |
| "detail": "File/state check passed", | |
| "num_tokens": 26, | |
| "response": "```bash\ncp app.conf app_prod.conf\nsed -i 's/DEBUG/ERROR/g' app_prod.conf\n```" | |
| }, | |
| { | |
| "id": "LINUX_02", | |
| "category": "Linux Commands", | |
| "prompt": "Write a single Linux bash pipeline that extracts the 2nd comma-separated column from `users.csv` (skipping the first header line), sorts the values alphabetically, and removes duplicates, printing to stdout. Return only the command.", | |
| "passed": false, | |
| "detail": "Got 'admin\\neditor\\nrole\\nuser', expected 'admin\\neditor\\nuser'", | |
| "num_tokens": 27, | |
| "response": "```bash\nawk -F, '{if ($2 != \"\") {print $2}}' users.csv | sort | uniq\n```" | |
| }, | |
| { | |
| "id": "LINUX_03", | |
| "category": "Linux Commands", | |
| "prompt": "Write a single Linux bash command or pipeline that counts how many lines in `server.log` contain the exact substring `500` and prints only that integer count to stdout. Return only the command.", | |
| "passed": true, | |
| "detail": "Stdout matched: '3'", | |
| "num_tokens": 15, | |
| "response": "```bash\ngrep -c '500' server.log\n```" | |
| }, | |
| { | |
| "id": "LINUX_04", | |
| "category": "Linux Commands", | |
| "prompt": "Write a single Linux bash pipeline that reads integers (one per line) from `nums.txt` and prints their total sum to stdout. Return only the command.", | |
| "passed": false, | |
| "detail": "Got '15\\n40\\n100\\n90', expected '90'", | |
| "num_tokens": 33, | |
| "response": "```bash\nwhile IFS= read -r line; do\n sum=$((sum + $line))\n echo \"$sum\"\ndone < nums.txt\n```" | |
| }, | |
| { | |
| "id": "LINUX_05", | |
| "category": "Linux Commands", | |
| "prompt": "Write a single Linux bash command using `chmod` to set the permissions of `deploy.sh` to `rwxr-x---` (owner read/write/execute, group read/execute, others no permissions). Return only the command.", | |
| "passed": false, | |
| "detail": "Exit 1: chmod: invalid mode: ‘rwxr-x---’\nTry 'chmod --help' for more information.", | |
| "num_tokens": 10, | |
| "response": "chmod -R rwxr-x--- deploy.sh" | |
| }, | |
| { | |
| "id": "LINUX_06", | |
| "category": "Linux Commands", | |
| "prompt": "Write a single Linux bash command using `find` or `ls`/`grep` that lists all `.py` filenames (just the file names or paths) inside the directory `src` (recursively) sorted alphabetically. Return only the command.", | |
| "passed": true, | |
| "detail": "Stdout check passed", | |
| "num_tokens": 25, | |
| "response": "```bash\nfind src -type f -name \"*.py\" | sort -t ' ' -k 1\n```" | |
| }, | |
| { | |
| "id": "LINUX_07", | |
| "category": "Linux Commands", | |
| "prompt": "Write a single Linux bash pipeline that reads `words.txt`, converts all uppercase letters to lowercase, sorts the lines alphabetically, and writes the result to `clean.txt`. Return only the command.", | |
| "passed": true, | |
| "detail": "File/state check passed", | |
| "num_tokens": 26, | |
| "response": "```bash\ncat words.txt | tr '[:upper:]' '[:lower:]' | sort | tee clean.txt\n```" | |
| }, | |
| { | |
| "id": "WEB_01", | |
| "category": "HTML / JS / CSS", | |
| "prompt": "Write a JavaScript function `function groupBy(arr, key)` that groups an array of objects `arr` by property `key` and returns an object mapping each key value to an array of matching objects. Return only the code.", | |
| "passed": true, | |
| "detail": "Passed Node.js tests", | |
| "num_tokens": 60, | |
| "response": "```javascript\nfunction groupBy(arr, key) {\n return arr.reduce((result, item) => {\n const value = item[key];\n if (!result[value]) {\n result[value] = [];\n }\n result[value].push(item);\n return result;\n }, {});\n}\n```" | |
| }, | |
| { | |
| "id": "WEB_02", | |
| "category": "HTML / JS / CSS", | |
| "prompt": "Write a JavaScript function `function chunkArray(arr, size)` that splits an array `arr` into chunks (subarrays) of length at most `size` and returns the array of chunks. Return only the code.", | |
| "passed": false, | |
| "detail": "Node error", | |
| "num_tokens": 36, | |
| "response": "```javascript\nfunction chunkArray(arr, size) {\n return arr.reduce((result, chunk) => {\n result.push(chunk);\n return result;\n }, []);\n}\n```" | |
| }, | |
| { | |
| "id": "WEB_03", | |
| "category": "HTML / JS / CSS", | |
| "prompt": "Write a JavaScript function `function parseQueryString(query)` that parses a URL query string like `\"?name=alice&age=30\"` into an object `{name: \"alice\", age: \"30\"}` (returning `{}` for empty string). Return only the code.", | |
| "passed": false, | |
| "detail": "Node error", | |
| "num_tokens": 58, | |
| "response": "```javascript\nfunction parseQueryString(query) {\n const obj = {};\n const parts = query.split('&');\n for (const part of parts) {\n const [key, value] = part.split('=');\n obj[key] = value;\n }\n return obj;\n}\n```" | |
| }, | |
| { | |
| "id": "WEB_04", | |
| "category": "HTML / JS / CSS", | |
| "prompt": "Write a JavaScript function `function flattenObject(obj, prefix = '')` that flattens a nested object into a single-level object with dot-separated keys (e.g. `{a: {b: 1}}` -> `{'a.b': 1}`). Return only the code.", | |
| "passed": false, | |
| "detail": "[eval]:14", | |
| "num_tokens": 90, | |
| "response": "```javascript\nfunction flattenObject(obj, prefix = '') {\n const result = {};\n \n // Traverse each key-value pair in the object\n for (const [key, value] of Object.entries(obj)) {\n // If the value is an object, recursively flatten it\n if (typeof value === 'object') {\n result[prefix + key] = flattenObject(value, prefix + key);\n } else {\n // If" | |
| }, | |
| { | |
| "id": "WEB_05", | |
| "category": "HTML / JS / CSS", | |
| "prompt": "Write a CSS rule for selector `.grid-container` that sets it to a CSS Grid layout with 3 equal-width columns (`1fr` each) and a gap of `16px`. Return only the CSS code.", | |
| "passed": true, | |
| "detail": "All CSS rules matched", | |
| "num_tokens": 34, | |
| "response": "```css\n.grid-container {\n display: grid;\n grid-template-columns: repeat(3, 1fr);\n gap: 16px;\n}\n```" | |
| }, | |
| { | |
| "id": "WEB_06", | |
| "category": "HTML / JS / CSS", | |
| "prompt": "Write a CSS rule for selector `.flex-center` that uses Flexbox to center its child elements both horizontally and vertically, with `min-height: 100vh`. Return only the CSS code.", | |
| "passed": true, | |
| "detail": "All CSS rules matched", | |
| "num_tokens": 35, | |
| "response": "```css\n.flex-center {\n display: flex;\n align-items: center;\n justify-content: center;\n min-height: 100vh;\n}\n```" | |
| }, | |
| { | |
| "id": "WEB_07", | |
| "category": "HTML / JS / CSS", | |
| "prompt": "Write a JavaScript function `function toggleActiveClass(el)` that toggles the class `'active'` on DOM element `el` and returns `true` if `'active'` is now present or `false` otherwise. Return only the code.", | |
| "passed": true, | |
| "detail": "Passed Node.js tests", | |
| "num_tokens": 20, | |
| "response": "```javascript\nfunction toggleActiveClass(el) {\n return el.classList.toggle('active');\n}\n```" | |
| }, | |
| { | |
| "id": "SYS_01", | |
| "category": "SQL / C / Data", | |
| "prompt": "Given a SQLite table `users(id, name)` and `orders(id, user_id, amount)`, write a SQL query that returns `name` and `SUM(amount)` for each user who has orders, ordered by the total amount descending. Return only the SQL query.", | |
| "passed": true, | |
| "detail": "Rows matched: [('Bob', 200), ('Alice', 120)]", | |
| "num_tokens": 38, | |
| "response": "```sql\nSELECT name, SUM(amount) AS total_amount\nFROM users\nJOIN orders ON users.id = orders.user_id\nGROUP BY users.id\nORDER BY total_amount DESC;\n```" | |
| }, | |
| { | |
| "id": "SYS_02", | |
| "category": "SQL / C / Data", | |
| "prompt": "Given a SQLite table `employees(id, name, department, salary)`, write a SQL query returning `department` and `AVG(salary)` for departments where the average salary is strictly greater than 60000, ordered by average salary descending. Return only the SQL query.", | |
| "passed": false, | |
| "detail": "Exception: misuse of aggregate: AVG()", | |
| "num_tokens": 39, | |
| "response": "```sql\nSELECT department, AVG(salary)\nFROM employees\nWHERE AVG(salary) > 60000\nGROUP BY department\nORDER BY AVG(salary) DESC;\n```" | |
| }, | |
| { | |
| "id": "SYS_03", | |
| "category": "SQL / C / Data", | |
| "prompt": "Given a SQLite table `products(id, name, category, price)`, write a SQL query returning `name` and `price` of the top 2 most expensive products in category `'Electronics'`, ordered by `price` descending. Return only the SQL query.", | |
| "passed": true, | |
| "detail": "Rows matched: [('Laptop', 1200), ('Phone', 800)]", | |
| "num_tokens": 28, | |
| "response": "```sql\nSELECT name, price\nFROM products\nWHERE category = 'Electronics'\nORDER BY price DESC\nLIMIT 2;\n```" | |
| }, | |
| { | |
| "id": "SYS_04", | |
| "category": "SQL / C / Data", | |
| "prompt": "Write a C function `int gcd(int a, int b)` that computes and returns the greatest common divisor of two positive integers `a` and `b`. Return only the C function.", | |
| "passed": true, | |
| "detail": "Compiled & passed C assertions", | |
| "num_tokens": 54, | |
| "response": "```c\nint gcd(int a, int b) {\n // Use Euclidean algorithm\n while (b != 0) {\n int temp = b;\n b = a % b;\n a = temp;\n }\n return a;\n}\n```" | |
| }, | |
| { | |
| "id": "SYS_05", | |
| "category": "SQL / C / Data", | |
| "prompt": "Write a C function `int count_ones(unsigned int n)` that returns the number of set bits (`1`s) in the binary representation of `n`. Return only the C function.", | |
| "passed": false, | |
| "detail": "C assertion failed", | |
| "num_tokens": 21, | |
| "response": "```c\nint count_ones(unsigned int n) {\n return n & 1;\n}\n```" | |
| }, | |
| { | |
| "id": "SYS_06", | |
| "category": "SQL / C / Data", | |
| "prompt": "Write a Python function `def extract_emails(text: str) -> list[str]:` using `re.findall` that extracts all email addresses of the form `user@domain.tld` (alphanumeric, dots, underscores, hyphens) from `text`. Return only the code.", | |
| "passed": false, | |
| "detail": "AssertionError", | |
| "num_tokens": 57, | |
| "response": "```python\nimport re\n\ndef extract_emails(text: str) -> list[str]:\n return re.findall(r'([a-zA-Z0-9._-]+@([a-zA-Z0-9.-]+\\.[a-zA-Z0-9-]+))', text)\n```" | |
| }, | |
| { | |
| "id": "SYS_07", | |
| "category": "SQL / C / Data", | |
| "prompt": "Write a Python function `def filter_adults(json_str: str) -> list[str]:` that parses a JSON array of objects `[{\"name\": ..., \"age\": ...}]` and returns a list of `name` strings for entries with `age >= 18` in their original order. Return only the code.", | |
| "passed": true, | |
| "detail": "Passed all assertions", | |
| "num_tokens": 51, | |
| "response": "```python\ndef filter_adults(json_str: str) -> list[str]:\n import json\n data = json.loads(json_str)\n return [entry[\"name\"] for entry in data if entry[\"age\"] >= 18]\n```" | |
| } | |
| ], | |
| "model": "Qwen/Qwen3-0.6B (Baseline Normal)", | |
| "category_breakdown": { | |
| "Python": { | |
| "passed": 1, | |
| "total": 7, | |
| "accuracy_percent": 14.29, | |
| "avg_tokens": 69.7 | |
| }, | |
| "Linux Commands": { | |
| "passed": 4, | |
| "total": 7, | |
| "accuracy_percent": 57.14, | |
| "avg_tokens": 23.1 | |
| }, | |
| "HTML / JS / CSS": { | |
| "passed": 4, | |
| "total": 7, | |
| "accuracy_percent": 57.14, | |
| "avg_tokens": 47.6 | |
| }, | |
| "SQL / C / Data": { | |
| "passed": 4, | |
| "total": 7, | |
| "accuracy_percent": 57.14, | |
| "avg_tokens": 41.1 | |
| } | |
| } | |
| } |