Instructions to use lparkourer10/minecraft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use lparkourer10/minecraft with Transformers:

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

pipe = pipeline("text-generation", model="lparkourer10/minecraft")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("lparkourer10/minecraft")
model = AutoModelForCausalLM.from_pretrained("lparkourer10/minecraft", 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=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use lparkourer10/minecraft with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "lparkourer10/minecraft"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "lparkourer10/minecraft",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/lparkourer10/minecraft

SGLang

How to use lparkourer10/minecraft 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 "lparkourer10/minecraft" \
    --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": "lparkourer10/minecraft",
		"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 "lparkourer10/minecraft" \
        --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": "lparkourer10/minecraft",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Desktop
Docker Model Runner
How to use lparkourer10/minecraft with Docker Model Runner:
```
docker model run hf.co/lparkourer10/minecraft
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

This model was trained using my minecraft wiki dataset which was made by scrapping the entire wiki. I hope this model answers nearly all your minecraft questions

PLEASE REDOWNLOAD THE MODEL AS IT HAS BEEN UPDATED

Downloads last month: 22

Safetensors

Model size

1B params

Tensor type

BF16

Model tree for lparkourer10/minecraft

Base model

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

Finetuned

(1847)

this model

Quantizations

1 model

lparkourer10
/

minecraft

Model tree for lparkourer10/minecraft

Dataset used to train lparkourer10/minecraft