Instructions to use DannyAI/phi4_african_history_lora_ds2_axolotl_merged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DannyAI/phi4_african_history_lora_ds2_axolotl_merged with Transformers:

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

pipe = pipeline("text-generation", model="DannyAI/phi4_african_history_lora_ds2_axolotl_merged", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("DannyAI/phi4_african_history_lora_ds2_axolotl_merged", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("DannyAI/phi4_african_history_lora_ds2_axolotl_merged", trust_remote_code=True, 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 DannyAI/phi4_african_history_lora_ds2_axolotl_merged with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DannyAI/phi4_african_history_lora_ds2_axolotl_merged"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DannyAI/phi4_african_history_lora_ds2_axolotl_merged",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/DannyAI/phi4_african_history_lora_ds2_axolotl_merged

SGLang

How to use DannyAI/phi4_african_history_lora_ds2_axolotl_merged 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 "DannyAI/phi4_african_history_lora_ds2_axolotl_merged" \
    --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": "DannyAI/phi4_african_history_lora_ds2_axolotl_merged",
		"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 "DannyAI/phi4_african_history_lora_ds2_axolotl_merged" \
        --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": "DannyAI/phi4_african_history_lora_ds2_axolotl_merged",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use DannyAI/phi4_african_history_lora_ds2_axolotl_merged with Docker Model Runner:
```
docker model run hf.co/DannyAI/phi4_african_history_lora_ds2_axolotl_merged
```

Model Card for Model ID

This is the merged version of LoRAfrica and base Phi4 Model

Base Model: microsoft/Phi-4-mini-instruct
Lora Model: DannyAI/phi4_african_history_lora_ds2_axolotl

Model Details

Model Description

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

Developed by: Daniel Ihenacho
Funded by: Daniel Ihenacho
Shared by: Daniel Ihenacho
Model type: Text Generation
Language(s) (NLP): English
License: mit
LoRA Model: DannyAI/phi4_african_history_lora_ds2_axolotl
Base Model: microsoft/Phi-4-mini-instruct

Uses

This can be used for QA datasets about African History

Out-of-Scope Use

Can be used beyond African History but should not.

How to Get Started with the Model

from transformers import pipeline
from transformers import (
    AutoTokenizer, 
    AutoModelForCausalLM)

model_id = "DannyAI/phi4_african_history_lora_ds2_axolotl_merged"

tokeniser = AutoTokenizer.from_pretrained(model_id)

# load merged model
model  = AutoModelForCausalLM.from_pretrained(
    model_id,
    device_map = "auto",
    torch_dtype = torch.bfloat16,
    trust_remote_code = False
)

generator = pipeline(
    "text-generation",
    model=model,
    tokenizer=tokeniser,
)
question = "What is the significance of African feminist scholarly activism in contemporary resistance movements?"
def generate_answer(question)->str:
    """Generates an answer for the given question using the fine-tuned LoRA model.
    """
    messages = [
        {"role": "system", "content": "You are a helpful AI assistant specialised in African history which gives concise answers to questions asked."},
        {"role": "user", "content": question}
    ]
    
    output = generator(
        messages, 
        max_new_tokens=2048, 
        temperature=0.1, 
        do_sample=False,
        return_full_text=False
    )
    return output[0]['generated_text'].strip()

# Example output
African feminist scholarly activism is significant in contemporary resistance movements as it provides a critical framework for understanding and addressing the specific challenges faced by African women in the context of global capitalism, neocolonialism, and patriarchal structures.

Citation

If you use this dataset, please cite:

@Model{
Ihenacho2026phi4_african_history_lora_ds2_axolotl_merged,
  author    = {Daniel Ihenacho},
  title     = {phi4_african_history_lora_ds2_axolotl_merged},
  year      = {2026},
  publisher = {Hugging Face Models},
  url       = {https://huggingface.co/DannyAI/phi4_african_history_lora_ds2_axolotl_merged},
  urldate   = {2026-03-21},
}

Model Card Authors

Daniel Ihenacho

Model Card Contact

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Safetensors

Model size

4B params

Tensor type

BF16

Model tree for DannyAI/phi4_african_history_lora_ds2_axolotl_merged

Base model

microsoft/Phi-4-mini-instruct

Adapter

DannyAI/phi4_african_history_lora_ds2_axolotl