Instructions to use dogtooting/Thoth-Q2_K-GGUF-split with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use dogtooting/Thoth-Q2_K-GGUF-split with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf dogtooting/Thoth-Q2_K-GGUF-split:Q2_K # Run inference directly in the terminal: llama cli -hf dogtooting/Thoth-Q2_K-GGUF-split:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf dogtooting/Thoth-Q2_K-GGUF-split:Q2_K # Run inference directly in the terminal: llama cli -hf dogtooting/Thoth-Q2_K-GGUF-split:Q2_K
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 dogtooting/Thoth-Q2_K-GGUF-split:Q2_K # Run inference directly in the terminal: ./llama-cli -hf dogtooting/Thoth-Q2_K-GGUF-split:Q2_K
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 dogtooting/Thoth-Q2_K-GGUF-split:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf dogtooting/Thoth-Q2_K-GGUF-split:Q2_K
Use Docker
docker model run hf.co/dogtooting/Thoth-Q2_K-GGUF-split:Q2_K
- LM Studio
- Jan
- Ollama
How to use dogtooting/Thoth-Q2_K-GGUF-split with Ollama:
ollama run hf.co/dogtooting/Thoth-Q2_K-GGUF-split:Q2_K
- Unsloth Desktop
- Docker Model Runner
How to use dogtooting/Thoth-Q2_K-GGUF-split with Docker Model Runner:
docker model run hf.co/dogtooting/Thoth-Q2_K-GGUF-split:Q2_K
- Lemonade
How to use dogtooting/Thoth-Q2_K-GGUF-split with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull dogtooting/Thoth-Q2_K-GGUF-split:Q2_K
Run and chat with the model
lemonade run user.Thoth-Q2_K-GGUF-split-Q2_K
List all available models
lemonade list
- Atomic Chat
Thoth Q2_K β split GGUF for in-browser inference
This repo contains Thoth.Q2_K.gguf from
mradermacher/Thoth-GGUF,
split into 6 shards of <480 MB each with llama-gguf-split so it can be
loaded in the browser by wllama (which has a
2 GB per-file ArrayBuffer limit).
The original model, Thoth, is a mergekit
merge of Mistral-7B-family models (32k context, SPM tokenizer). The base repo
CoprolaliacPress/Thoth has since been removed, so these quants from
mradermacher are the only surviving copy.
Files
| File | Size |
|---|---|
Thoth.Q2_K-00001-of-00006.gguf |
472 MB |
Thoth.Q2_K-00002-of-00006.gguf |
479 MB |
Thoth.Q2_K-00003-of-00006.gguf |
476 MB |
Thoth.Q2_K-00004-of-00006.gguf |
474 MB |
Thoth.Q2_K-00005-of-00006.gguf |
461 MB |
Thoth.Q2_K-00006-of-00006.gguf |
357 MB |
Total β 2.72 GB, byte-identical to the source Thoth.Q2_K.gguf when merged.
Usage
Browser (wllama): pass the URL of shard 00001 β it pulls the rest automatically.
await wllama.loadModelFromUrl(
"https://huggingface.co/dogtooting/Thoth-Q2_K-GGUF-split/resolve/main/Thoth.Q2_K-00001-of-00006.gguf"
);
llama.cpp: point -m at shard 00001, or merge first:
llama-gguf-split --merge Thoth.Q2_K-00001-of-00006.gguf Thoth.Q2_K.gguf
Prompt format
ChatML (as plain text β these are not special tokens in the vocab):
<|im_start|>system
{system}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
Stop on <|im_end|>.
Live demo: dogtooting/Thoth-GGUF-Chat
- Downloads last month
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2-bit
Model tree for dogtooting/Thoth-Q2_K-GGUF-split
Base model
mradermacher/Thoth-GGUF