Instructions to use justindal/llama3.2-3b-leetcoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use justindal/llama3.2-3b-leetcoder with MLX:

# Make sure mlx-lm is installed
# pip install --upgrade mlx-lm

# Generate text with mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("justindal/llama3.2-3b-leetcoder")

prompt = "Write a story about Einstein"
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
    messages, add_generation_prompt=True
)

text = generate(model, tokenizer, prompt=prompt, verbose=True)

Notebooks
Google Colab
Kaggle
Local Apps Settings
LM Studio

How to use justindal/llama3.2-3b-leetcoder with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "justindal/llama3.2-3b-leetcoder"

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "mlx-lm": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "justindal/llama3.2-3b-leetcoder"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use justindal/llama3.2-3b-leetcoder with Hermes Agent:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "justindal/llama3.2-3b-leetcoder"

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 justindal/llama3.2-3b-leetcoder

Run Hermes

hermes

MLX LM

How to use justindal/llama3.2-3b-leetcoder with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "justindal/llama3.2-3b-leetcoder"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "justindal/llama3.2-3b-leetcoder"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "justindal/llama3.2-3b-leetcoder",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

justindal commited on about 1 month ago

Commit

e9118f0

verified ·

1 Parent(s): 8abc1b4

Add files using upload-large-folder tool

Browse files

Files changed (4) hide show

README.md +0 -1
chat_template.jinja +6 -2
model-00001-of-00002.safetensors +1 -1
model-00002-of-00002.safetensors +1 -1

README.md CHANGED Viewed

@@ -59,4 +59,3 @@ prompt = "Given an integer array nums, return indices of two numbers that add up
 response = generate(model, tokenizer, prompt=prompt)
 print(response)
 ```

 response = generate(model, tokenizer, prompt=prompt)
 print(response)
 ```

chat_template.jinja CHANGED Viewed

@@ -16,7 +16,7 @@
     {%- set tools = none %}
 {%- endif %}
-{#- This block extracts the system message, so we can slot it into the right place. #}
 {%- if messages[0]['role'] == 'system' %}
     {%- set system_message = messages[0]['content']|trim %}
     {%- set messages = messages[1:] %}
@@ -66,7 +66,11 @@
 {%- for message in messages %}
     {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
-        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
     {%- elif 'tool_calls' in message %}
         {%- if not message.tool_calls|length == 1 %}
             {{- raise_exception("This model only supports single tool-calls at once!") }}

     {%- set tools = none %}
 {%- endif %}
+{}
 {%- if messages[0]['role'] == 'system' %}
     {%- set system_message = messages[0]['content']|trim %}
     {%- set messages = messages[1:] %}
 {%- for message in messages %}
     {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
+        {%- if message.role == 'assistant' and message.reasoning is defined and message.reasoning %}
+            {{- '<|start_header_id|>assistant<|end_header_id|>\n\n<think>\n' + message.reasoning | trim + '\n</think>\n\n' + message['content'] | trim + '<|eot_id|>' }}
+        {%- else %}
+            {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
+        {%- endif %}
     {%- elif 'tool_calls' in message %}
         {%- if not message.tool_calls|length == 1 %}
             {{- raise_exception("This model only supports single tool-calls at once!") }}

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