Instructions to use SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF",
	filename="TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T.Q4_K_M.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF:Q4_K_M

Use pre-built binary

# 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 SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF:Q4_K_M

Build from source code

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 SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF:Q4_K_M

Use Docker

docker model run hf.co/SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF with Ollama:
```
ollama run hf.co/SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF:Q4_K_M
```

Unsloth Studio

How to use SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

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 SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF to start chatting

Install Unsloth Studio (Windows)

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 SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF with Docker Model Runner:
```
docker model run hf.co/SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF:Q4_K_M
```

Lemonade

How to use SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull SlimeQ/TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF-Q4_K_M

List all available models

lemonade list

TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T-Q4_K_M-GGUF / TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T.Q4_K_M.gguf

SlimeQ

Upload TinyLlama_TinyLlama-1.1B-intermediate-step-955k-token-2T.Q4_K_M.gguf

5767b12 over 2 years ago

download

history blame GGUF Editor new delete

668 MB

This file is stored with Xet . It is too big to display, but you can still download it.

Xet Pointer Details

( Raw pointer file )

Xet hash:: afbaa3cca2fc36a8de2202ee71e062fc112a11bfdc8f11a86897219f53a8832c
Size of remote file:: 668 MB
SHA256:: 26e9bac45c2e536c309d6efe16ac178bfecab1438ae8ab6fcb8af2a24e8caea1

Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.