Text Classification
GGUF
English
llama.cpp
decision-model
multiple-choice
typesafe
qwen3.5
conversational
Instructions to use DreamBlooms/Tev1-0.8B-experimental-GGUF 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 DreamBlooms/Tev1-0.8B-experimental-GGUF 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 DreamBlooms/Tev1-0.8B-experimental-GGUF:Q8_0 # Run inference directly in the terminal: llama cli -hf DreamBlooms/Tev1-0.8B-experimental-GGUF:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf DreamBlooms/Tev1-0.8B-experimental-GGUF:Q8_0 # Run inference directly in the terminal: llama cli -hf DreamBlooms/Tev1-0.8B-experimental-GGUF:Q8_0
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 DreamBlooms/Tev1-0.8B-experimental-GGUF:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf DreamBlooms/Tev1-0.8B-experimental-GGUF:Q8_0
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 DreamBlooms/Tev1-0.8B-experimental-GGUF:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf DreamBlooms/Tev1-0.8B-experimental-GGUF:Q8_0
Use Docker
docker model run hf.co/DreamBlooms/Tev1-0.8B-experimental-GGUF:Q8_0
- LM Studio
- Jan
- Ollama
How to use DreamBlooms/Tev1-0.8B-experimental-GGUF with Ollama:
ollama run hf.co/DreamBlooms/Tev1-0.8B-experimental-GGUF:Q8_0
- Unsloth Desktop
- Pi
How to use DreamBlooms/Tev1-0.8B-experimental-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf DreamBlooms/Tev1-0.8B-experimental-GGUF:Q8_0
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "DreamBlooms/Tev1-0.8B-experimental-GGUF:Q8_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use DreamBlooms/Tev1-0.8B-experimental-GGUF with Docker Model Runner:
docker model run hf.co/DreamBlooms/Tev1-0.8B-experimental-GGUF:Q8_0
- Lemonade
How to use DreamBlooms/Tev1-0.8B-experimental-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull DreamBlooms/Tev1-0.8B-experimental-GGUF:Q8_0
Run and chat with the model
lemonade run user.Tev1-0.8B-experimental-GGUF-Q8_0
List all available models
lemonade list
- Hermes Agent
How to use DreamBlooms/Tev1-0.8B-experimental-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf DreamBlooms/Tev1-0.8B-experimental-GGUF:Q8_0
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default DreamBlooms/Tev1-0.8B-experimental-GGUF:Q8_0
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use DreamBlooms/Tev1-0.8B-experimental-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf DreamBlooms/Tev1-0.8B-experimental-GGUF:Q8_0
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "DreamBlooms/Tev1-0.8B-experimental-GGUF:Q8_0" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Upload README.md with huggingface_hub
Browse files
README.md
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---
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base_model: togethercomputer/Tev1-0.8B-experimental
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language:
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- en
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library_name: llama.cpp
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pipeline_tag: text-generation
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tags:
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- decision-model
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- gguf
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- qwen3.5
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- tev1
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---
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# Tev1-0.8B-experimental GGUF
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Quantized GGUF conversions of
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[togethercomputer/Tev1-0.8B-experimental](https://huggingface.co/togethercomputer/Tev1-0.8B-experimental),
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an experimental Qwen3.5-0.8B decision model from Together AI. It is a supervised
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fine-tune trained to choose one option from a structured state, question, and a
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list of 2-24 labeled choices, returning a single option letter.
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These files run with [dohnuts.cpp](https://github.com/DreamBlooms/dohnuts.cpp)
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through its `tev1` profile.
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| File | Quantization |
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| --- | --- |
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| `tev1-f16.gguf` | F16 |
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| `tev1-Q8_0.gguf` | Q8_0 |
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`tev1.json` (the profile config) is required alongside the GGUF:
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```sh
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build/dohnuts-cli --model tev1-0.8b-q8_0.gguf --metadata tev1.json
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```
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## Conversion
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A full fine-tune, converted directly:
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```sh
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scripts/build_tev1_gguf.sh <tev1-0.8b-dir> work/side/tev1-0.8b-q8_0.gguf
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```
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## License
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The base Qwen3.5-0.8B model is Apache-2.0. The upstream release license for the
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fine-tuned weights is being finalized; see the upstream model card for the
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current terms.
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