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
```

Remek commited on Sep 6, 2024

Commit

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+---
+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
+---
+<p align="center">
+  <img src="https://huggingface.co/speakleash/Bielik-7B-Instruct-v0.1/raw/main/speakleash_cyfronet.png">
+</p>
+# Bielik-11B-v2.2-Instruct-GPTQ
+This repo contains GPTQ format model files for [SpeakLeash](https://speakleash.org/)'s [Bielik-11B-v.2.0-Instruct](https://huggingface.co/speakleash/Bielik-11B-v2.0-Instruct).
+<b><u>DISCLAIMER: Be aware that quantised models show reduced response quality and possible hallucinations!</u></b><br>
+### Model description:
+* **Developed by:** [SpeakLeash](https://speakleash.org/) & [ACK Cyfronet AGH](https://www.cyfronet.pl/)
+* **Language:** Polish
+* **Model type:** causal decoder-only
+* **Quant from:** [Bielik-11B-v2.0-Instruct](https://huggingface.co/speakleash/Bielik-11B-v2.0-Instruct)
+* **Finetuned from:** [Bielik-11B-v2](https://huggingface.co/speakleash/Bielik-11B-v2)
+* **License:** Apache 2.0 and [Terms of Use](https://bielik.ai/terms/)
+### Responsible for model quantization
+* [Remigiusz Kinas](https://www.linkedin.com/in/remigiusz-kinas/)<sup>SpeakLeash</sup> - 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](https://discord.gg/CPBxPce4).