Instructions to use Davizig10jojo/BlazerApex-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Davizig10jojo/BlazerApex-2B with Transformers:

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

pipe = pipeline("text-generation", model="Davizig10jojo/BlazerApex-2B")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Davizig10jojo/BlazerApex-2B", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Davizig10jojo/BlazerApex-2B with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Davizig10jojo/BlazerApex-2B:IQ4_XS
# Run inference directly in the terminal:
llama cli -hf Davizig10jojo/BlazerApex-2B:IQ4_XS

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Davizig10jojo/BlazerApex-2B:IQ4_XS
# Run inference directly in the terminal:
llama cli -hf Davizig10jojo/BlazerApex-2B:IQ4_XS

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf Davizig10jojo/BlazerApex-2B:IQ4_XS
# Run inference directly in the terminal:
./llama-cli -hf Davizig10jojo/BlazerApex-2B:IQ4_XS

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf Davizig10jojo/BlazerApex-2B:IQ4_XS
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Davizig10jojo/BlazerApex-2B:IQ4_XS

Use Docker

docker model run hf.co/Davizig10jojo/BlazerApex-2B:IQ4_XS

LM Studio
Jan

vLLM

How to use Davizig10jojo/BlazerApex-2B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Davizig10jojo/BlazerApex-2B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Davizig10jojo/BlazerApex-2B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Davizig10jojo/BlazerApex-2B:IQ4_XS

SGLang

How to use Davizig10jojo/BlazerApex-2B 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 "Davizig10jojo/BlazerApex-2B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Davizig10jojo/BlazerApex-2B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "Davizig10jojo/BlazerApex-2B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Davizig10jojo/BlazerApex-2B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Ollama
How to use Davizig10jojo/BlazerApex-2B with Ollama:
```
ollama run hf.co/Davizig10jojo/BlazerApex-2B:IQ4_XS
```
Unsloth Desktop
Docker Model Runner
How to use Davizig10jojo/BlazerApex-2B with Docker Model Runner:
```
docker model run hf.co/Davizig10jojo/BlazerApex-2B:IQ4_XS
```

Lemonade

How to use Davizig10jojo/BlazerApex-2B with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Davizig10jojo/BlazerApex-2B:IQ4_XS

Run and chat with the model

lemonade run user.BlazerApex-2B-IQ4_XS

List all available models

lemonade list

Atomic Chat

Davizig10jojo commited on 7 days ago

Commit

98d2642

verified ·

1 Parent(s): 82fd0d8

Create Notas_do_benchmark.json

Browse files

Files changed (1) hide show

Notas_do_benchmark.json +6 -0

Notas_do_benchmark.json ADDED Viewed

	@@ -0,0 +1,6 @@

+======================================================================
+RESULTADOS FINAIS (avaliados por juiz Qwen3-4B-Instruct)
+======================================================================
+Qwen2.5-3B           média  97.5/100  | [95, 100, 100, 95, 95, 100, 100, 95]
+BlazerApex-2B        média  88.1/100  | [30, 100, 95, 95, 95, 100, 95, 95]
+MiniCPM5-2B          média  75.0/100  | [30, 100, 85, 75, 30, 100, 85, 95]