Instructions to use speakleash/Bielik-11B-v2.0-Instruct-GPTQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use speakleash/Bielik-11B-v2.0-Instruct-GPTQ with Transformers:

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

pipe = pipeline("text-generation", model="speakleash/Bielik-11B-v2.0-Instruct-GPTQ")
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("speakleash/Bielik-11B-v2.0-Instruct-GPTQ")
model = AutoModelForCausalLM.from_pretrained("speakleash/Bielik-11B-v2.0-Instruct-GPTQ", 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 speakleash/Bielik-11B-v2.0-Instruct-GPTQ with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "speakleash/Bielik-11B-v2.0-Instruct-GPTQ"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "speakleash/Bielik-11B-v2.0-Instruct-GPTQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/speakleash/Bielik-11B-v2.0-Instruct-GPTQ

SGLang

How to use speakleash/Bielik-11B-v2.0-Instruct-GPTQ 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 "speakleash/Bielik-11B-v2.0-Instruct-GPTQ" \
    --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": "speakleash/Bielik-11B-v2.0-Instruct-GPTQ",
		"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 "speakleash/Bielik-11B-v2.0-Instruct-GPTQ" \
        --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": "speakleash/Bielik-11B-v2.0-Instruct-GPTQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use speakleash/Bielik-11B-v2.0-Instruct-GPTQ with Docker Model Runner:
```
docker model run hf.co/speakleash/Bielik-11B-v2.0-Instruct-GPTQ
```

Bielik-11B-v2.0-Instruct-GPTQ / README.md

chrisociepa

Update README.md

b27c987 verified about 2 years ago

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metadata

language:
  - pl
license: apache-2.0
library_name: transformers
tags:
  - finetuned
  - gguf
inference: false
pipeline_tag: text-generation
base_model: speakleash/Bielik-11B-v2.0-Instruct

Bielik-11B-v2.0-Instruct-GPTQ

This repo contains GPTQ format model files for SpeakLeash's Bielik-11B-v.2.0-Instruct.

DISCLAIMER: Be aware that quantised models show reduced response quality and possible hallucinations!

Model description:

Developed by: SpeakLeash & ACK Cyfronet AGH
Language: Polish
Model type: causal decoder-only
Quant from: Bielik-11B-v2.0-Instruct
Finetuned from: Bielik-11B-v2
License: Apache 2.0 and Terms of Use

Responsible for model quantization

Remigiusz Kinas^SpeakLeash - team leadership, conceptualizing, calibration data preparation, process creation and quantized model delivery.

Contact Us

If you have any questions or suggestions, please use the discussion tab. If you want to contact us directly, join our Discord SpeakLeash.