Instructions to use mrsandip/Alfa-Code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mrsandip/Alfa-Code with Transformers:

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

pipe = pipeline("text-generation", model="mrsandip/Alfa-Code")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("mrsandip/Alfa-Code", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use mrsandip/Alfa-Code 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 mrsandip/Alfa-Code:Q4_0
# Run inference directly in the terminal:
llama cli -hf mrsandip/Alfa-Code:Q4_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf mrsandip/Alfa-Code:Q4_0
# Run inference directly in the terminal:
llama cli -hf mrsandip/Alfa-Code:Q4_0

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf mrsandip/Alfa-Code:Q4_0
# Run inference directly in the terminal:
./build/bin/llama cli -hf mrsandip/Alfa-Code:Q4_0

Use Docker

docker model run hf.co/mrsandip/Alfa-Code:Q4_0

Llama new
LM Studio
Jan

vLLM

How to use mrsandip/Alfa-Code with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/mrsandip/Alfa-Code:Q4_0

SGLang

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

Ollama
How to use mrsandip/Alfa-Code with Ollama:
```
ollama run hf.co/mrsandip/Alfa-Code:Q4_0
```
Unsloth Desktop
Docker Model Runner
How to use mrsandip/Alfa-Code with Docker Model Runner:
```
docker model run hf.co/mrsandip/Alfa-Code:Q4_0
```

Lemonade

How to use mrsandip/Alfa-Code with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull mrsandip/Alfa-Code:Q4_0

Run and chat with the model

lemonade run user.Alfa-Code-Q4_0

List all available models

lemonade list

Atomic Chat

mrsandip commited on Oct 14

Commit

a0519cf

verified ·

1 Parent(s): e294ba1

.manifest

Browse files

Files changed (1) hide show

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-.e-commerce/
-├── .gitignore
-├── app/
-│   ├── [locale]/
-│   │   ├── catalog/
-│   │   │   ├── category/
-│   │   │   │   └── [slug]/
-│   │   │   │       └── page.tsx
-│   │   │   └── product/
-│   │   │       └── [slug]/
-│   │   │           └── page.tsx
-│   │   ├── layout.tsx
-│   │   └── page.tsx
-│   ├── favicon.ico
-│   ├── globals.css
-│   ├── layout.tsx
-│   ├── page.tsx
-│   └── page.module.css
-├── components/
-│   ├── ui/
-│   │   ├── avatar.tsx
-│   │   ├── badge.tsx
-│   │   ├── button.tsx
-│   │   ├── card.tsx
-│   │   ├── checkbox.tsx
-│   │   ├── dialog.tsx
-│   │   ├── dropdown-menu.tsx
-│   │   ├── index.ts
-│   │   ├── input.tsx
-│   │   ├── label.tsx
-│   │   ├── popover.tsx
-│   │   ├── radio-group.tsx
-│   │   ├── scroll-area.tsx
-│   │   ├── select.tsx
-│   │   ├── separator.tsx
-│   │   ├── switch.tsx
-│   │   ├── tooltip.tsx
-│   │   └── ...
-│   └── ...
-├── db/
-│   ├── apply-schema.sql
-│   ├── index.ts
-│   ├── push.ts
-│   ├── schema.ts
-│   ├── verify-queries.sql
-│   └── verify-seed.ts
-├── drizzle.config.ts
-├── i18n/
-│   ├── request.ts
-│   └── routing.ts
-├── lib/
-│   ├── format-inr.ts
-│   ├── money.ts
-│   └── utils.ts
-├── messages/
-│   ├── bn.json
-│   └── en.json
-├── next.config.ts
-├── package.json
-├── package-lock.json
-├── postcss.config.mjs
-├── proxy.ts
-├── scripts/
-│   └── seed.ts
-├── tailwind.config.ts
-├── tmp/
-│   └── ...
-├── tsconfig.json
-└── biome.json