Instructions to use ghananlpcommunity/opani-coder_1b-merged-16bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ghananlpcommunity/opani-coder_1b-merged-16bit with Transformers:

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

pipe = pipeline("text-generation", model="ghananlpcommunity/opani-coder_1b-merged-16bit")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ghananlpcommunity/opani-coder_1b-merged-16bit")
model = AutoModelForCausalLM.from_pretrained("ghananlpcommunity/opani-coder_1b-merged-16bit")
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

vLLM

How to use ghananlpcommunity/opani-coder_1b-merged-16bit with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ghananlpcommunity/opani-coder_1b-merged-16bit"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ghananlpcommunity/opani-coder_1b-merged-16bit",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ghananlpcommunity/opani-coder_1b-merged-16bit

SGLang

How to use ghananlpcommunity/opani-coder_1b-merged-16bit 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 "ghananlpcommunity/opani-coder_1b-merged-16bit" \
    --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": "ghananlpcommunity/opani-coder_1b-merged-16bit",
		"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 "ghananlpcommunity/opani-coder_1b-merged-16bit" \
        --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": "ghananlpcommunity/opani-coder_1b-merged-16bit",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio new

How to use ghananlpcommunity/opani-coder_1b-merged-16bit with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for ghananlpcommunity/opani-coder_1b-merged-16bit to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for ghananlpcommunity/opani-coder_1b-merged-16bit to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for ghananlpcommunity/opani-coder_1b-merged-16bit to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="ghananlpcommunity/opani-coder_1b-merged-16bit",
    max_seq_length=2048,
)

Docker Model Runner
How to use ghananlpcommunity/opani-coder_1b-merged-16bit with Docker Model Runner:
```
docker model run hf.co/ghananlpcommunity/opani-coder_1b-merged-16bit
```

Opani Coder 1B (16-bit)

A fine-tuned Llama 3.2 1B model for coding assistance in Twi (Akan language), helping Twi speakers learn programming in their native language.

Model Details

Base Model: Llama 3.2 1B
Precision: 16-bit full model
Language: Twi with code examples
Fine-tuning: Full model fine-tuning
Developed by: michsethowusu

Installation

pip install torch transformers

Usage

You can test the model using this HF Space - https://huggingface.co/spaces/michsethowusu/Opani-Coder-DEMO

from transformers import AutoTokenizer, AutoModelForCausalLM, TextStreamer
import torch

# Load model
model_id = "michsethowusu/opani-coder_1b-merged-16bit"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.float16,
    device_map="auto",
)

# Prepare message
messages = [
    {"role": "user", "content": "Kyerɛkyerɛ nea for loop yɛ"}
]

text = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True,
)

# Generate response
streamer = TextStreamer(tokenizer, skip_prompt=True)
_ = model.generate(
    **tokenizer(text, return_tensors="pt").to(model.device),
    max_new_tokens=512,
    temperature=0.7,
    top_p=0.9,
    streamer=streamer,
)

Use Cases

Explaining programming concepts in Twi
Code generation with Twi commentary
Debugging assistance in Twi
Translating coding tutorials to Twi

Limitations

Optimized for Twi language programming interactions
May mix English technical terms
Verify generated code before production use

Citation

@misc{opani-coder_1b_2024,
  author = {michsethowusu},
  title = {Opani Coder 1B: Fine-tuned Llama 3.2 1B for Twi Coding Assistance},
  year = {2024},
  publisher = {HuggingFace},
  url = {https://huggingface.co/michsethowusu/opani-coder_1b-merged-16bit}
}

Contact

HuggingFace: @michsethowusu

Downloads last month: 11

Safetensors

Model size

1B params

Tensor type

BF16

Model tree for ghananlpcommunity/opani-coder_1b-merged-16bit

Base model

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

Finetuned

(1747)

this model

ghananlpcommunity
/

opani-coder_1b-merged-16bit