Instructions to use Fate-Zero/Archer-Code-1.5B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Fate-Zero/Archer-Code-1.5B with Transformers:

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

pipe = pipeline("text-generation", model="Fate-Zero/Archer-Code-1.5B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Fate-Zero/Archer-Code-1.5B")
model = AutoModelForCausalLM.from_pretrained("Fate-Zero/Archer-Code-1.5B", 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 Fate-Zero/Archer-Code-1.5B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Fate-Zero/Archer-Code-1.5B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Fate-Zero/Archer-Code-1.5B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Fate-Zero/Archer-Code-1.5B

SGLang

How to use Fate-Zero/Archer-Code-1.5B 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 "Fate-Zero/Archer-Code-1.5B" \
    --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": "Fate-Zero/Archer-Code-1.5B",
		"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 "Fate-Zero/Archer-Code-1.5B" \
        --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": "Fate-Zero/Archer-Code-1.5B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Fate-Zero/Archer-Code-1.5B with Docker Model Runner:
```
docker model run hf.co/Fate-Zero/Archer-Code-1.5B
```

Improve model card: Add metadata tags and sample usage

by nielsr HF Staff - opened Jul 22, 2025

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+48

-0

nielsr

Jul 22, 2025

This PR improves the model card by:

Adding pipeline_tag: text-generation to ensure the model appears in relevant searches on the Hugging Face Hub and enables the text-generation widget.
Adding library_name: transformers to correctly associate the model with the Hugging Face Transformers library, allowing users to easily load it with AutoModelForCausalLM.
Adding relevant tags: reasoning, code-generation, math, and qwen2 for better discoverability, aligning with the model's capabilities described in the paper abstract and evaluation.
Including a "Sample Usage" section with a basic Python code snippet using the transformers library, which will greatly enhance the model's usability for inference.

The existing link to the arXiv paper is maintained as per instructions, and other content remains unchanged.

Improve model card: Add metadata tags and sample usagee6049f27

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