Instructions to use large-traversaal/Alif-1.0-8B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use large-traversaal/Alif-1.0-8B-Instruct with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("large-traversaal/Alif-1.0-8B-Instruct", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use large-traversaal/Alif-1.0-8B-Instruct 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 large-traversaal/Alif-1.0-8B-Instruct:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf large-traversaal/Alif-1.0-8B-Instruct:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf large-traversaal/Alif-1.0-8B-Instruct:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf large-traversaal/Alif-1.0-8B-Instruct:Q4_K_M

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 large-traversaal/Alif-1.0-8B-Instruct:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf large-traversaal/Alif-1.0-8B-Instruct:Q4_K_M

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 large-traversaal/Alif-1.0-8B-Instruct:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf large-traversaal/Alif-1.0-8B-Instruct:Q4_K_M

Use Docker

docker model run hf.co/large-traversaal/Alif-1.0-8B-Instruct:Q4_K_M

LM Studio
Jan
Ollama
How to use large-traversaal/Alif-1.0-8B-Instruct with Ollama:
```
ollama run hf.co/large-traversaal/Alif-1.0-8B-Instruct:Q4_K_M
```

Unsloth Studio

How to use large-traversaal/Alif-1.0-8B-Instruct 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 large-traversaal/Alif-1.0-8B-Instruct 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 large-traversaal/Alif-1.0-8B-Instruct to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for large-traversaal/Alif-1.0-8B-Instruct to start chatting

Docker Model Runner
How to use large-traversaal/Alif-1.0-8B-Instruct with Docker Model Runner:
```
docker model run hf.co/large-traversaal/Alif-1.0-8B-Instruct:Q4_K_M
```

Lemonade

How to use large-traversaal/Alif-1.0-8B-Instruct with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull large-traversaal/Alif-1.0-8B-Instruct:Q4_K_M

Run and chat with the model

lemonade run user.Alif-1.0-8B-Instruct-Q4_K_M

List all available models

lemonade list

Atomic Chat

Improve model card: Add pipeline_tag, library_name, and resource links

by nielsr HF Staff - opened Oct 13, 2025

base: refs/heads/main

←

from: refs/pr/3

Discussion Files changed

+15

-14

Files changed (1) hide show

README.md +15 -14

README.md CHANGED Viewed

@@ -1,27 +1,29 @@
 ---
 base_model: unsloth/Meta-Llama-3.1-8B
 tags:
 - text-generation-inference
-- transformers
 - unsloth
 - llama
 - trl
-license: apache-2.0
-language:
-- en
-- ur
 ---
 # Model Card for Alif 1.0 8B Instruct
-**Alif 1.0 8B Instruct** is an open-source model with highly advanced multilingual reasoning capabilities. It utilizes human refined multilingual synthetic data paired with reasoning to enhance cultural nuance and reasoning capabilities in english and urdu languages.
-- **Developed by:** large-traversaal
-- **License:** apache-2.0
-- **Base model:** unsloth/Meta-Llama-3.1-8B
-- **Model:** Alif-1.0-8B-Instruct
-- **Model Size:** 8 billion parameters
 This model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
@@ -103,5 +105,4 @@ We evaluated Alif 1.0 8B Instruct against Gemma 2 9B, Llama 3.1 8B, Mistral Nemo
 ### Model Card Contact
-For errors or additional questions about details in this model card, contact: contact@traversaal.ai

 ---
 base_model: unsloth/Meta-Llama-3.1-8B
+language:
+- en
+- ur
+license: apache-2.0
+pipeline_tag: text-generation
+library_name: transformers
 tags:
 - text-generation-inference
 - unsloth
 - llama
 - trl
 ---
 # Model Card for Alif 1.0 8B Instruct
+[[Paper](https://huggingface.co/papers/2510.09051)] [[Code](https://github.com/traversaal-ai/alif-urdu-llm)] [[Datasets](https://huggingface.co/datasets/large-traversaal/urdu-instruct)] [[Blog](https://blog.traversaal.ai/announcing-alif-1-0-our-first-urdu-llm-outperforming-other-open-source-llms/)] [[Live Demo](https://huggingface.co/spaces/large-traversaal/Alif-1.0-8B-Instruct)]
+**Alif 1.0 8B Instruct** is an open-source model with highly advanced multilingual reasoning capabilities. It utilizes human refined multilingual synthetic data paired with reasoning to enhance cultural nuance and reasoning capabilities in english and urdu languages. This model was presented in the paper [Alif: Advancing Urdu Large Language Models via Multilingual Synthetic Data Distillation](https://huggingface.co/papers/2510.09051).
+-   **Developed by:** large-traversaal
+-   **License:** apache-2.0
+-   **Base model:** unsloth/Meta-Llama-3.1-8B
+-   **Model:** Alif-1.0-8B-Instruct
+-   **Model Size:** 8 billion parameters
 This model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
 ### Model Card Contact
+For errors or additional questions about details in this model card, contact: contact@traversaal.ai