Instructions to use positron-ai/Llama-3.2-1B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use positron-ai/Llama-3.2-1B-Instruct with Transformers:

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

pipe = pipeline("text-generation", model="positron-ai/Llama-3.2-1B-Instruct")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("positron-ai/Llama-3.2-1B-Instruct")
model = AutoModelForCausalLM.from_pretrained("positron-ai/Llama-3.2-1B-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]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use positron-ai/Llama-3.2-1B-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "positron-ai/Llama-3.2-1B-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": "positron-ai/Llama-3.2-1B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/positron-ai/Llama-3.2-1B-Instruct

SGLang

How to use positron-ai/Llama-3.2-1B-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 "positron-ai/Llama-3.2-1B-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": "positron-ai/Llama-3.2-1B-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 "positron-ai/Llama-3.2-1B-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": "positron-ai/Llama-3.2-1B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use positron-ai/Llama-3.2-1B-Instruct with Docker Model Runner:
```
docker model run hf.co/positron-ai/Llama-3.2-1B-Instruct
```

Llama-3.2-1B-Instruct (unmodified redistribution)

Built with Llama.

This is an unmodified redistribution of meta-llama/Llama-3.2-1B-Instruct at upstream commit e9f8effbab1cbdc515c11ee6e098e3d5a9f51e14. Weights, tokenizer, and configuration files are byte-identical to that commit (SHA256s below); only this README and the NOTICE file were added.

Positron AI redistributes this snapshot as the pinned source for the GPTQ quantizations it publishes under the positron-ai organization.

Model documentation, evaluations, and responsible-use guidance: see Meta's original model card linked above.

Provenance

file	sha256
model.safetensors	1ff795ff6a07e6a68085d206fb84417da2f083f68391c2843cd2b8ac6df8538f

License

Use of this model is governed by the Llama 3.2 Community License Agreement and Meta's Acceptable Use Policy, both included in this repository. See NOTICE. All model documentation, benchmarks, and responsible-use guidance are at the upstream model card linked above.

Downloads last month: 402

Safetensors

Model size

1B params

Tensor type

BF16

Model tree for positron-ai/Llama-3.2-1B-Instruct

Base model

meta-llama/Llama-3.2-1B-Instruct

Finetuned

(1803)

this model