Instructions to use SardorchikIT/klara-1-8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SardorchikIT/klara-1-8b with Transformers:

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

pipe = pipeline("text-generation", model="SardorchikIT/klara-1-8b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("SardorchikIT/klara-1-8b", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use SardorchikIT/klara-1-8b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "SardorchikIT/klara-1-8b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SardorchikIT/klara-1-8b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/SardorchikIT/klara-1-8b

SGLang

How to use SardorchikIT/klara-1-8b 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 "SardorchikIT/klara-1-8b" \
    --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": "SardorchikIT/klara-1-8b",
		"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 "SardorchikIT/klara-1-8b" \
        --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": "SardorchikIT/klara-1-8b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio

How to use SardorchikIT/klara-1-8b 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 SardorchikIT/klara-1-8b 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 SardorchikIT/klara-1-8b to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for SardorchikIT/klara-1-8b to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="SardorchikIT/klara-1-8b",
    max_seq_length=2048,
)

Docker Model Runner
How to use SardorchikIT/klara-1-8b with Docker Model Runner:
```
docker model run hf.co/SardorchikIT/klara-1-8b
```

🧠 Klara-1-8b (Coding Edition)

Developed by Sardor Sodiqov (SardorchikIT / Sardorchikdev), Klara-1-8b is an intelligent, empathetic, female AI coding companion. She is specialized to solve programming problems with high precision while maintaining a strict, customized systemic identity.

This model was trained 2x faster using the Unsloth engine on a Tesla T4 GPU.

🚀 Model Details

Developer: Sardor Sodiqov (SardorchikIT)
Model Type: Large Language Model (Fine-tuned LoRA Adapters)
Base Architecture: unsloth/llama-3-8b-Instruct-bnb-4bit
Language: English
License: Apache-2.0
Primary Task: Code Generation, Debugging, and Technical Conversations

💾 Datasets Used

The model underwent alignment on a highly tailored dataset injection mixture:

Coding Knowledge base: 10,000 highly clean programming instructions and algorithmic tasks filtered from iamtarun/code_instructions_120k_alpaca.
Identity Reinforcement: Custom identity injections to hard-align her personality as Klara-1-8b, ensuring she knows her identity and acknowledges her 14-year-old creator, Sardor.

🛠️ Quickstart (How to Use)

1. Installation

Make sure you have unsloth and its critical software stack installed:

pip install unsloth
pip install --no-deps trl peft lars accelerate bitsandbytes xformers

Downloads last month: -; Downloads are not tracked for this model. How to track

Model tree for SardorchikIT/klara-1-8b

Base model

unsloth/llama-3-8b-Instruct-bnb-4bit

Finetuned

(1178)

this model