Instructions to use braindao/iq-code-evmind-v3-granite-8b-instruct-beginner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use braindao/iq-code-evmind-v3-granite-8b-instruct-beginner with Transformers:

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

pipe = pipeline("text-generation", model="braindao/iq-code-evmind-v3-granite-8b-instruct-beginner")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("braindao/iq-code-evmind-v3-granite-8b-instruct-beginner")
model = AutoModelForCausalLM.from_pretrained("braindao/iq-code-evmind-v3-granite-8b-instruct-beginner")
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 braindao/iq-code-evmind-v3-granite-8b-instruct-beginner with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "braindao/iq-code-evmind-v3-granite-8b-instruct-beginner"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "braindao/iq-code-evmind-v3-granite-8b-instruct-beginner",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/braindao/iq-code-evmind-v3-granite-8b-instruct-beginner

SGLang

How to use braindao/iq-code-evmind-v3-granite-8b-instruct-beginner 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 "braindao/iq-code-evmind-v3-granite-8b-instruct-beginner" \
    --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": "braindao/iq-code-evmind-v3-granite-8b-instruct-beginner",
		"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 "braindao/iq-code-evmind-v3-granite-8b-instruct-beginner" \
        --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": "braindao/iq-code-evmind-v3-granite-8b-instruct-beginner",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use braindao/iq-code-evmind-v3-granite-8b-instruct-beginner with Docker Model Runner:
```
docker model run hf.co/braindao/iq-code-evmind-v3-granite-8b-instruct-beginner
```

The LLM "braindao/iq-code-evmind-v3-granite-8b-instruct-beginner" is a specialized model fine-tuned for generating Solidity code.

It is based on the "ibm-granite/granite-8b-code-instruct" model and has been further trained using the "braindao/Solidity-Dataset", specifically utilizing the "beginner" column of the dataset.

This model is designed to assist with Solidity programming tasks, particularly catering to beginners in blockchain and smart contract development.

Its focus on Solidity makes it a potentially valuable tool for those learning or working with Ethereum-based smart contracts.

Downloads last month: 3

Safetensors

Model size

8B params

Tensor type

F16

braindao
/

iq-code-evmind-v3-granite-8b-instruct-beginner

Dataset used to train braindao/iq-code-evmind-v3-granite-8b-instruct-beginner