Local Models
Collection
16 items • Updated • 1
How to use cortexso/tinyllama with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="cortexso/tinyllama", filename="tinyllama-1.1b-chat-v1.0-q2_k.gguf", )
llm.create_chat_completion(
messages = [
{
"role": "user",
"content": "What is the capital of France?"
}
]
)How to use cortexso/tinyllama with llama.cpp:
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf cortexso/tinyllama:Q4_K_M # Run inference directly in the terminal: llama-cli -hf cortexso/tinyllama:Q4_K_M
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf cortexso/tinyllama:Q4_K_M # Run inference directly in the terminal: llama-cli -hf cortexso/tinyllama:Q4_K_M
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf cortexso/tinyllama:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf cortexso/tinyllama:Q4_K_M
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf cortexso/tinyllama:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf cortexso/tinyllama:Q4_K_M
docker model run hf.co/cortexso/tinyllama:Q4_K_M
How to use cortexso/tinyllama with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "cortexso/tinyllama"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "cortexso/tinyllama",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'docker model run hf.co/cortexso/tinyllama:Q4_K_M
How to use cortexso/tinyllama with Ollama:
ollama run hf.co/cortexso/tinyllama:Q4_K_M
How to use cortexso/tinyllama with Unsloth Studio:
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 cortexso/tinyllama to start chatting
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 cortexso/tinyllama to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for cortexso/tinyllama to start chatting
How to use cortexso/tinyllama with Docker Model Runner:
docker model run hf.co/cortexso/tinyllama:Q4_K_M
How to use cortexso/tinyllama with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull cortexso/tinyllama:Q4_K_M
lemonade run user.tinyllama-Q4_K_M
lemonade list
The TinyLlama project aims to pretrain a 1.1B Llama model on 3 trillion tokens. This is the chat model finetuned on a diverse range of synthetic dialogues generated by ChatGPT.
| No | Variant | Cortex CLI command |
|---|---|---|
| 1 | TinyLLama-1b | cortex run tinyllama:1b |
cortexhub/tinyllama
cortex run tinyllama
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