Instructions to use mlx-community/Llama-3.2-3B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mlx-community/Llama-3.2-3B-Instruct with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="mlx-community/Llama-3.2-3B-Instruct")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("mlx-community/Llama-3.2-3B-Instruct")
model = AutoModelForCausalLM.from_pretrained("mlx-community/Llama-3.2-3B-Instruct", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

MLX

How to use mlx-community/Llama-3.2-3B-Instruct 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("mlx-community/Llama-3.2-3B-Instruct")

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

vLLM

How to use mlx-community/Llama-3.2-3B-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mlx-community/Llama-3.2-3B-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mlx-community/Llama-3.2-3B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/mlx-community/Llama-3.2-3B-Instruct

SGLang

How to use mlx-community/Llama-3.2-3B-Instruct 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 "mlx-community/Llama-3.2-3B-Instruct" \
    --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": "mlx-community/Llama-3.2-3B-Instruct",
		"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 "mlx-community/Llama-3.2-3B-Instruct" \
        --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": "mlx-community/Llama-3.2-3B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

How to use mlx-community/Llama-3.2-3B-Instruct with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "mlx-community/Llama-3.2-3B-Instruct"

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": "mlx-community/Llama-3.2-3B-Instruct"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use mlx-community/Llama-3.2-3B-Instruct with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "mlx-community/Llama-3.2-3B-Instruct"

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 "mlx-community/Llama-3.2-3B-Instruct" \
  --custom-provider-id mlx-lm \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

MLX LM

How to use mlx-community/Llama-3.2-3B-Instruct with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "mlx-community/Llama-3.2-3B-Instruct"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "mlx-community/Llama-3.2-3B-Instruct"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "mlx-community/Llama-3.2-3B-Instruct",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Docker Model Runner
How to use mlx-community/Llama-3.2-3B-Instruct with Docker Model Runner:
```
docker model run hf.co/mlx-community/Llama-3.2-3B-Instruct
```

Hermes Agent

How to use mlx-community/Llama-3.2-3B-Instruct 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 "mlx-community/Llama-3.2-3B-Instruct"

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 mlx-community/Llama-3.2-3B-Instruct

Run Hermes

hermes

Llama-3.2-3B-Instruct / README.md

cmcmaster

Upload folder using huggingface_hub (#1)

96e4e2c verified almost 2 years ago

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	---
	base_model: meta-llama/Llama-3.2-3B-Instruct
	language:
	- en
	- de
	- fr
	- it
	- pt
	- hi
	- es
	- th
	library_name: transformers
	license: llama3.2
	pipeline_tag: text-generation
	tags:
	- facebook
	- meta
	- pytorch
	- llama
	- llama-3
	- mlx
	extra_gated_prompt: "### LLAMA 3.2 COMMUNITY LICENSE AGREEMENT\n\nLlama 3.2 Version\
	\ Release Date: September 25, 2024\n\n“Agreement” means the terms and conditions\
	\ for use, reproduction, distribution and modification of the Llama Materials set\
	\ forth herein.\n\n“Documentation” means the specifications, manuals and documentation\
	\ accompanying Llama 3.2 distributed by Meta at https://llama.meta.com/doc/overview.\n\
	\n“Licensee” or “you” means you, or your employer or any other person or entity\
	\ (if you are entering into this Agreement on such person or entity’s behalf),\
	\ of the age required under applicable laws, rules or regulations to provide legal\
	\ consent and that has legal authority to bind your employer or such other person\
	\ or entity if you are entering in this Agreement on their behalf.\n\n“Llama 3.2”\
	\ means the foundational large language models and software and algorithms, including\
	\ machine-learning model code, trained model weights, inference-enabling code, training-enabling\
	\ code, fine-tuning enabling code and other elements of the foregoing distributed\
	\ by Meta at https://www.llama.com/llama-downloads.\n\n“Llama Materials” means,\
	\ collectively, Meta’s proprietary Llama 3.2 and Documentation (and any portion\
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	\ Ireland Limited (if you are located in or, if you are an entity, your principal\
	\ place of business is in the EEA or Switzerland) and Meta Platforms, Inc. (if\
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	\ below or by using or distributing any portion or element of the Llama Materials,\
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	a. Grant of Rights. You are granted a non-exclusive, worldwide, non-transferable\
	\ and royalty-free limited license under Meta’s intellectual property or other rights\
	\ owned by Meta embodied in the Llama Materials to use, reproduce, distribute,\
	\ copy, create derivative works of, and make modifications to the Llama Materials.\
	\ \nb. Redistribution and Use. \ni. If you distribute or make available the Llama\
	\ Materials (or any derivative works thereof), or a product or service (including\
	\ another AI model) that contains any of them, you shall (A) provide a copy of this\
	\ Agreement with any such Llama Materials; and (B) prominently display “Built with\
	\ Llama” on a related website, user interface, blogpost, about page, or product\
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	\ Llama Materials to create, train, fine tune, or otherwise improve an AI model,\
	\ which is distributed or made available, you shall also include “Llama” at the\
	\ beginning of any such AI model name.\nii. If you receive Llama Materials, or any\
	\ derivative works thereof, from a Licensee as part of an integrated end user product,\
	\ then Section 2 of this Agreement will not apply to you. \niii. You must retain\
	\ in all copies of the Llama Materials that you distribute the following attribution\
	\ notice within a “Notice” text file distributed as a part of such copies: “Llama\
	\ 3.2 is licensed under the Llama 3.2 Community License, Copyright © Meta Platforms,\
	\ Inc. All Rights Reserved.”\niv. Your use of the Llama Materials must comply with\
	\ applicable laws and regulations (including trade compliance laws and regulations)\
	\ and adhere to the Acceptable Use Policy for the Llama Materials (available at\
	\ https://www.llama.com/llama3_2/use-policy), which is hereby incorporated by reference\
	\ into this Agreement.\n \n2. Additional Commercial Terms. If, on the Llama 3.2\
	\ version release date, the monthly active users of the products or services made\
	\ available by or for Licensee, or Licensee’s affiliates, is greater than 700 million\
	\ monthly active users in the preceding calendar month, you must request a license\
	\ from Meta, which Meta may grant to you in its sole discretion, and you are not\
	\ authorized to exercise any of the rights under this Agreement unless or until\
	\ Meta otherwise expressly grants you such rights.\n3. Disclaimer of Warranty. UNLESS\
	\ REQUIRED BY APPLICABLE LAW, THE LLAMA MATERIALS AND ANY OUTPUT AND RESULTS THEREFROM\
	\ ARE PROVIDED ON AN “AS IS” BASIS, WITHOUT WARRANTIES OF ANY KIND, AND META DISCLAIMS\
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	a. No trademark licenses are granted under this Agreement, and in connection with\
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	\ or as set forth in this Section 5(a). Meta hereby grants you a license to use\
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	\ https://about.meta.com/brand/resources/meta/company-brand/). All goodwill arising\
	\ out of your use of the Mark will inure to the benefit of Meta.\nb. Subject to\
	\ Meta’s ownership of Llama Materials and derivatives made by or for Meta, with\
	\ respect to any derivative works and modifications of the Llama Materials that\
	\ are made by you, as between you and Meta, you are and will be the owner of such\
	\ derivative works and modifications.\nc. If you institute litigation or other proceedings\
	\ against Meta or any entity (including a cross-claim or counterclaim in a lawsuit)\
	\ alleging that the Llama Materials or Llama 3.2 outputs or results, or any portion\
	\ of any of the foregoing, constitutes infringement of intellectual property or\
	\ other rights owned or licensable by you, then any licenses granted to you under\
	\ this Agreement shall terminate as of the date such litigation or claim is filed\
	\ or instituted. You will indemnify and hold harmless Meta from and against any\
	\ claim by any third party arising out of or related to your use or distribution\
	\ of the Llama Materials.\n6. Term and Termination. The term of this Agreement will\
	\ commence upon your acceptance of this Agreement or access to the Llama Materials\
	\ and will continue in full force and effect until terminated in accordance with\
	\ the terms and conditions herein. Meta may terminate this Agreement if you are\
	\ in breach of any term or condition of this Agreement. Upon termination of this\
	\ Agreement, you shall delete and cease use of the Llama Materials. Sections 3,\
	\ 4 and 7 shall survive the termination of this Agreement. \n7. Governing Law and\
	\ Jurisdiction. This Agreement will be governed and construed under the laws of\
	\ the State of California without regard to choice of law principles, and the UN\
	\ Convention on Contracts for the International Sale of Goods does not apply to\
	\ this Agreement. The courts of California shall have exclusive jurisdiction of\
	\ any dispute arising out of this Agreement. \n### Llama 3.2 Acceptable Use Policy\n\
	Meta is committed to promoting safe and fair use of its tools and features, including\
	\ Llama 3.2. If you access or use Llama 3.2, you agree to this Acceptable Use Policy\
	\ (“Policy”). The most recent copy of this policy can be found at [https://www.llama.com/llama3_2/use-policy](https://www.llama.com/llama3_2/use-policy).\n\
	#### Prohibited Uses\nWe want everyone to use Llama 3.2 safely and responsibly.\
	\ You agree you will not use, or allow others to use, Llama 3.2 to:\n1. Violate\
	\ the law or others’ rights, including to:\n 1. Engage in, promote, generate,\
	\ contribute to, encourage, plan, incite, or further illegal or unlawful activity\
	\ or content, such as:\n 1. Violence or terrorism\n 2. Exploitation\
	\ or harm to children, including the solicitation, creation, acquisition, or dissemination\
	\ of child exploitative content or failure to report Child Sexual Abuse Material\n\
	\ 3. Human trafficking, exploitation, and sexual violence\n 4. The\
	\ illegal distribution of information or materials to minors, including obscene\
	\ materials, or failure to employ legally required age-gating in connection with\
	\ such information or materials.\n 5. Sexual solicitation\n 6. Any\
	\ other criminal activity\n 1. Engage in, promote, incite, or facilitate the\
	\ harassment, abuse, threatening, or bullying of individuals or groups of individuals\n\
	\ 2. Engage in, promote, incite, or facilitate discrimination or other unlawful\
	\ or harmful conduct in the provision of employment, employment benefits, credit,\
	\ housing, other economic benefits, or other essential goods and services\n 3.\
	\ Engage in the unauthorized or unlicensed practice of any profession including,\
	\ but not limited to, financial, legal, medical/health, or related professional\
	\ practices\n 4. Collect, process, disclose, generate, or infer private or sensitive\
	\ information about individuals, including information about individuals’ identity,\
	\ health, or demographic information, unless you have obtained the right to do so\
	\ in accordance with applicable law\n 5. Engage in or facilitate any action or\
	\ generate any content that infringes, misappropriates, or otherwise violates any\
	\ third-party rights, including the outputs or results of any products or services\
	\ using the Llama Materials\n 6. Create, generate, or facilitate the creation\
	\ of malicious code, malware, computer viruses or do anything else that could disable,\
	\ overburden, interfere with or impair the proper working, integrity, operation\
	\ or appearance of a website or computer system\n 7. Engage in any action, or\
	\ facilitate any action, to intentionally circumvent or remove usage restrictions\
	\ or other safety measures, or to enable functionality disabled by Meta \n2. Engage\
	\ in, promote, incite, facilitate, or assist in the planning or development of activities\
	\ that present a risk of death or bodily harm to individuals, including use of Llama\
	\ 3.2 related to the following:\n 8. Military, warfare, nuclear industries or\
	\ applications, espionage, use for materials or activities that are subject to the\
	\ International Traffic Arms Regulations (ITAR) maintained by the United States\
	\ Department of State or to the U.S. Biological Weapons Anti-Terrorism Act of 1989\
	\ or the Chemical Weapons Convention Implementation Act of 1997\n 9. Guns and\
	\ illegal weapons (including weapon development)\n 10. Illegal drugs and regulated/controlled\
	\ substances\n 11. Operation of critical infrastructure, transportation technologies,\
	\ or heavy machinery\n 12. Self-harm or harm to others, including suicide, cutting,\
	\ and eating disorders\n 13. Any content intended to incite or promote violence,\
	\ abuse, or any infliction of bodily harm to an individual\n3. Intentionally deceive\
	\ or mislead others, including use of Llama 3.2 related to the following:\n 14.\
	\ Generating, promoting, or furthering fraud or the creation or promotion of disinformation\n\
	\ 15. Generating, promoting, or furthering defamatory content, including the\
	\ creation of defamatory statements, images, or other content\n 16. Generating,\
	\ promoting, or further distributing spam\n 17. Impersonating another individual\
	\ without consent, authorization, or legal right\n 18. Representing that the\
	\ use of Llama 3.2 or outputs are human-generated\n 19. Generating or facilitating\
	\ false online engagement, including fake reviews and other means of fake online\
	\ engagement \n4. Fail to appropriately disclose to end users any known dangers\
	\ of your AI system 5. Interact with third party tools, models, or software designed\
	\ to generate unlawful content or engage in unlawful or harmful conduct and/or represent\
	\ that the outputs of such tools, models, or software are associated with Meta or\
	\ Llama 3.2\n\nWith respect to any multimodal models included in Llama 3.2, the\
	\ rights granted under Section 1(a) of the Llama 3.2 Community License Agreement\
	\ are not being granted to you if you are an individual domiciled in, or a company\
	\ with a principal place of business in, the European Union. This restriction does\
	\ not apply to end users of a product or service that incorporates any such multimodal\
	\ models.\n\nPlease report any violation of this Policy, software “bug,” or other\
	\ problems that could lead to a violation of this Policy through one of the following\
	\ means:\n\n* Reporting issues with the model: [https://github.com/meta-llama/llama-models/issues](https://l.workplace.com/l.php?u=https%3A%2F%2Fgithub.com%2Fmeta-llama%2Fllama-models%2Fissues&h=AT0qV8W9BFT6NwihiOHRuKYQM_UnkzN_NmHMy91OT55gkLpgi4kQupHUl0ssR4dQsIQ8n3tfd0vtkobvsEvt1l4Ic6GXI2EeuHV8N08OG2WnbAmm0FL4ObkazC6G_256vN0lN9DsykCvCqGZ)\n\
	* Reporting risky content generated by the model: [developers.facebook.com/llama_output_feedback](http://developers.facebook.com/llama_output_feedback)\n\
	* Reporting bugs and security concerns: [facebook.com/whitehat/info](http://facebook.com/whitehat/info)\n\
	* Reporting violations of the Acceptable Use Policy or unlicensed uses of Llama\
	\ 3.2: LlamaUseReport@meta.com"
	extra_gated_fields:
	First Name: text
	Last Name: text
	Date of birth: date_picker
	Country: country
	Affiliation: text
	Job title:
	type: select
	options:
	- Student
	- Research Graduate
	- AI researcher
	- AI developer/engineer
	- Reporter
	- Other
	geo: ip_location
	? By clicking Submit below I accept the terms of the license and acknowledge that
	the information I provide will be collected stored processed and shared in accordance
	with the Meta Privacy Policy
	: checkbox
	extra_gated_description: The information you provide will be collected, stored, processed
	and shared in accordance with the [Meta Privacy Policy](https://www.facebook.com/privacy/policy/).
	extra_gated_button_content: Submit
	---

	# mlx-community/Llama-3.2-3B-Instruct

	The Model [mlx-community/Llama-3.2-3B-Instruct](https://huggingface.co/mlx-community/Llama-3.2-3B-Instruct) was converted to MLX format from [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) using mlx-lm version 0.18.2.

	## Use with mlx

	```bash
	pip install mlx-lm
	```

	```python
	from mlx_lm import load, generate

	model, tokenizer = load("mlx-community/Llama-3.2-3B-Instruct")

	prompt="hello"

	if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
	messages = [{"role": "user", "content": prompt}]
	prompt = tokenizer.apply_chat_template(
	messages, tokenize=False, add_generation_prompt=True
	)

	response = generate(model, tokenizer, prompt=prompt, verbose=True)
	```