Instructions to use Keynote-Technology/TinyKAI-1B-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Keynote-Technology/TinyKAI-1B-v0.1 with Transformers:

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

pipe = pipeline("text-generation", model="Keynote-Technology/TinyKAI-1B-v0.1", trust_remote_code=True)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Keynote-Technology/TinyKAI-1B-v0.1", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("Keynote-Technology/TinyKAI-1B-v0.1", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Keynote-Technology/TinyKAI-1B-v0.1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Keynote-Technology/TinyKAI-1B-v0.1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Keynote-Technology/TinyKAI-1B-v0.1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Keynote-Technology/TinyKAI-1B-v0.1

SGLang

How to use Keynote-Technology/TinyKAI-1B-v0.1 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 "Keynote-Technology/TinyKAI-1B-v0.1" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Keynote-Technology/TinyKAI-1B-v0.1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "Keynote-Technology/TinyKAI-1B-v0.1" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Keynote-Technology/TinyKAI-1B-v0.1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Keynote-Technology/TinyKAI-1B-v0.1 with Docker Model Runner:
```
docker model run hf.co/Keynote-Technology/TinyKAI-1B-v0.1
```

TinyKAI-1B-v0.1 / README.md

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	---
	license: apache-2.0
	tags:
	- code
	- chatbot
	datasets:
	- Keynote-Technology/PLANE-2K
	- togethercomputer/RedPajama-Data-V2
	---
	## TinyKAI 1B

	![image/png](https://cdn-uploads.huggingface.co/production/uploads/6500c7c912c1442d994c36e5/gr9lrm53Tp52ehU5009lU.png)

	TinyKAI 1B is a fine-tuned LLM (Large Language Model) based off of Falcon-rw-1B.

	### Direct Use
	TinyKAI 1B is optimal for research on large language models, specifically the influence of web data on the properties of large language models (fairness, safety, limitations, capabilities, etc.).

	### Banned Use

	Production use without adequate assessment of risks and mitigation; any use cases which may be considered irresponsible or harmful.

	## Limitations

	TinyKAI 1B is trained on English data only, and will not generate appropriately reasonable content in other languages. Being trained on a representative of the web, it will carry the stereotypes and biases commonly encountered online. In addition, KAI-1B has a very low output limit (less than 2 thousand characters) and struggles when asked to quote online sources.

	## Recommendations

	We recommend users of TinyKAI 1B to consider finetuning it for personal use, and for precautions to be taken for any commercial use.

	## Banned Use
	TinyKAI-1B is governed by the [apache 2.0 liscense](https://choosealicense.com/licenses/apache-2.0/), and therefore means that whatever the license deems unacceptable shall not be allowed. We specificaly ban the use of [ANY AND ALL KAI MODELS](https://huggingface.co/collections/Keynote-Technology/kai-large-language-models) for hate speech towards a paricular thing, person, our particular group due to [legal](https://www.ftc.gov/news-events/news/press-releases/2022/06/ftc-report-warns-about-using-artificial-intelligence-combat-online-problems) and ethical issues.