Instructions to use mstyslavity/5tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mstyslavity/5tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="mstyslavity/5tiny")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("mstyslavity/5tiny") model = AutoModelForCausalLM.from_pretrained("mstyslavity/5tiny") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use mstyslavity/5tiny with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "mstyslavity/5tiny" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mstyslavity/5tiny", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/mstyslavity/5tiny
- SGLang
How to use mstyslavity/5tiny 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 "mstyslavity/5tiny" \ --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": "mstyslavity/5tiny", "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 "mstyslavity/5tiny" \ --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": "mstyslavity/5tiny", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use mstyslavity/5tiny with Docker Model Runner:
docker model run hf.co/mstyslavity/5tiny
metadata
base_model:
- Jiayi-Pan/Tiny-Vicuna-1B
- yihanwang617/tinyllama-sft-vicuna-random-100k
- QuixiAI/TinyDolphin-2.8.2-1.1b
- TinyLlama/TinyLlama-1.1B-Chat-v1.0
- NickyNicky/cognitivecomputations_TinyDolphin-2.8-1.1b
library_name: transformers
tags:
- mergekit
- merge
merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the Linear merge method.
Models Merged
The following models were included in the merge:
- Jiayi-Pan/Tiny-Vicuna-1B
- yihanwang617/tinyllama-sft-vicuna-random-100k
- QuixiAI/TinyDolphin-2.8.2-1.1b
- TinyLlama/TinyLlama-1.1B-Chat-v1.0
- NickyNicky/cognitivecomputations_TinyDolphin-2.8-1.1b
Configuration
The following YAML configuration was used to produce this model:
models:
- model: Jiayi-Pan/Tiny-Vicuna-1B
parameters:
weight: 0.2
- model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
parameters:
weight: 0.2
- model: yihanwang617/tinyllama-sft-vicuna-random-100k
parameters:
weight: 0.2
- model: NickyNicky/cognitivecomputations_TinyDolphin-2.8-1.1b
parameters:
weight: 0.2
- model: QuixiAI/TinyDolphin-2.8.2-1.1b
parameters:
weight: 0.2
merge_method: linear
dtype: float32