Instructions to use neuracoder/neuracoder-tiny-1.1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use neuracoder/neuracoder-tiny-1.1b with Transformers:

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

pipe = pipeline("text-generation", model="neuracoder/neuracoder-tiny-1.1b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("neuracoder/neuracoder-tiny-1.1b")
model = AutoModelForMultimodalLM.from_pretrained("neuracoder/neuracoder-tiny-1.1b")
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 neuracoder/neuracoder-tiny-1.1b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "neuracoder/neuracoder-tiny-1.1b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "neuracoder/neuracoder-tiny-1.1b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/neuracoder/neuracoder-tiny-1.1b

SGLang

How to use neuracoder/neuracoder-tiny-1.1b 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 "neuracoder/neuracoder-tiny-1.1b" \
    --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": "neuracoder/neuracoder-tiny-1.1b",
		"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 "neuracoder/neuracoder-tiny-1.1b" \
        --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": "neuracoder/neuracoder-tiny-1.1b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use neuracoder/neuracoder-tiny-1.1b with Docker Model Runner:
```
docker model run hf.co/neuracoder/neuracoder-tiny-1.1b
```

neuracoder commited on 12 days ago

Commit

0076499

verified ·

1 Parent(s): 23da4cf

Update README.md

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@@ -18,37 +18,6 @@ tags:
 - humaneval
 - mbpp
 pipeline_tag: text-generation
-datasets:
-- TheStack
-- CodeSearchNet
-- bigcode/the-stack-dedup
-- nuprl/MultiPL-E
-metrics:
-- code_eval
-- pass@1
-- pass@10
-- bleu
----
----
-language:
-- en
-- code
-license: apache-2.0
-library_name: transformers
-tags:
-- code
-- text-generation
-- llama
-- instruct
-- code-generation
-- python
-- lightweight
-- iranian-company
-- neuracoder
-- benchmark
-- humaneval
-- mbpp
-pipeline_tag: text-generation
 base_model: llama
 datasets:
 - TheStack

 - humaneval
 - mbpp
 pipeline_tag: text-generation
 base_model: llama
 datasets:
 - TheStack