Instructions to use tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF", dtype="auto") - llama-cpp-python
How to use tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF", filename="OpenThoughts3_1.5B-Q2_K.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-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 tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF: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 tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF:Q2_K # Run inference directly in the terminal: ./llama-cli -hf tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF: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 tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF:Q2_K
Use Docker
docker model run hf.co/tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF:Q2_K
- LM Studio
- Jan
- Ollama
How to use tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF with Ollama:
ollama run hf.co/tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF:Q2_K
- Unsloth Studio
How to use tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-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 tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-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 tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF to start chatting
- Pi
How to use tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF:Q2_K
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF:Q2_K" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-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 tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF:Q2_K
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 tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF:Q2_K
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF:Q2_K
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 "tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF:Q2_K" \ --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"
- Docker Model Runner
How to use tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF with Docker Model Runner:
docker model run hf.co/tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF:Q2_K
- Lemonade
How to use tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF:Q2_K
Run and chat with the model
lemonade run user.mlfoundations-dev_OpenThoughts3_1.5B-GGUF-Q2_K
List all available models
lemonade list
0fd9a6c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 | ---
library_name: transformers
license: other
base_model: mlfoundations-dev/OpenThoughts3_1.5B
tags:
- llama-factory
- full
- generated_from_trainer
- TensorBlock
- GGUF
model-index:
- name: OpenThoughts3_1.5B
results: []
---
<div style="width: auto; margin-left: auto; margin-right: auto">
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</div>
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## mlfoundations-dev/OpenThoughts3_1.5B - GGUF
<div style="text-align: left; margin: 20px 0;">
<a href="https://discord.com/invite/Ej5NmeHFf2" style="display: inline-block; padding: 10px 20px; background-color: #5865F2; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
Join our Discord to learn more about what we're building β
</a>
</div>
This repo contains GGUF format model files for [mlfoundations-dev/OpenThoughts3_1.5B](https://huggingface.co/mlfoundations-dev/OpenThoughts3_1.5B).
The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b5753](https://github.com/ggml-org/llama.cpp/commit/73e53dc834c0a2336cd104473af6897197b96277).
## Our projects
<table border="1" cellspacing="0" cellpadding="10">
<tr>
<th colspan="2" style="font-size: 25px;">Forge</th>
</tr>
<tr>
<th colspan="2">
<img src="https://imgur.com/faI5UKh.jpeg" alt="Forge Project" width="900"/>
</th>
</tr>
<tr>
<th colspan="2">An OpenAI-compatible multi-provider routing layer.</th>
</tr>
<tr>
<th colspan="2">
<a href="https://github.com/TensorBlock/forge" target="_blank" style="
display: inline-block;
padding: 8px 16px;
background-color: #FF7F50;
color: white;
text-decoration: none;
border-radius: 6px;
font-weight: bold;
font-family: sans-serif;
">π Try it now! π</a>
</th>
</tr>
<tr>
<th style="font-size: 25px;">Awesome MCP Servers</th>
<th style="font-size: 25px;">TensorBlock Studio</th>
</tr>
<tr>
<th><img src="https://imgur.com/2Xov7B7.jpeg" alt="MCP Servers" width="450"/></th>
<th><img src="https://imgur.com/pJcmF5u.jpeg" alt="Studio" width="450"/></th>
</tr>
<tr>
<th>A comprehensive collection of Model Context Protocol (MCP) servers.</th>
<th>A lightweight, open, and extensible multi-LLM interaction studio.</th>
</tr>
<tr>
<th>
<a href="https://github.com/TensorBlock/awesome-mcp-servers" target="_blank" style="
display: inline-block;
padding: 8px 16px;
background-color: #FF7F50;
color: white;
text-decoration: none;
border-radius: 6px;
font-weight: bold;
font-family: sans-serif;
">π See what we built π</a>
</th>
<th>
<a href="https://github.com/TensorBlock/TensorBlock-Studio" target="_blank" style="
display: inline-block;
padding: 8px 16px;
background-color: #FF7F50;
color: white;
text-decoration: none;
border-radius: 6px;
font-weight: bold;
font-family: sans-serif;
">π See what we built π</a>
</th>
</tr>
</table>
## Prompt template
```
<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
```
## Model file specification
| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [OpenThoughts3_1.5B-Q2_K.gguf](https://huggingface.co/tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF/blob/main/OpenThoughts3_1.5B-Q2_K.gguf) | Q2_K | 0.676 GB | smallest, significant quality loss - not recommended for most purposes |
| [OpenThoughts3_1.5B-Q3_K_S.gguf](https://huggingface.co/tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF/blob/main/OpenThoughts3_1.5B-Q3_K_S.gguf) | Q3_K_S | 0.761 GB | very small, high quality loss |
| [OpenThoughts3_1.5B-Q3_K_M.gguf](https://huggingface.co/tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF/blob/main/OpenThoughts3_1.5B-Q3_K_M.gguf) | Q3_K_M | 0.824 GB | very small, high quality loss |
| [OpenThoughts3_1.5B-Q3_K_L.gguf](https://huggingface.co/tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF/blob/main/OpenThoughts3_1.5B-Q3_K_L.gguf) | Q3_K_L | 0.880 GB | small, substantial quality loss |
| [OpenThoughts3_1.5B-Q4_0.gguf](https://huggingface.co/tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF/blob/main/OpenThoughts3_1.5B-Q4_0.gguf) | Q4_0 | 0.935 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [OpenThoughts3_1.5B-Q4_K_S.gguf](https://huggingface.co/tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF/blob/main/OpenThoughts3_1.5B-Q4_K_S.gguf) | Q4_K_S | 0.940 GB | small, greater quality loss |
| [OpenThoughts3_1.5B-Q4_K_M.gguf](https://huggingface.co/tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF/blob/main/OpenThoughts3_1.5B-Q4_K_M.gguf) | Q4_K_M | 0.986 GB | medium, balanced quality - recommended |
| [OpenThoughts3_1.5B-Q5_0.gguf](https://huggingface.co/tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF/blob/main/OpenThoughts3_1.5B-Q5_0.gguf) | Q5_0 | 1.099 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [OpenThoughts3_1.5B-Q5_K_S.gguf](https://huggingface.co/tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF/blob/main/OpenThoughts3_1.5B-Q5_K_S.gguf) | Q5_K_S | 1.099 GB | large, low quality loss - recommended |
| [OpenThoughts3_1.5B-Q5_K_M.gguf](https://huggingface.co/tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF/blob/main/OpenThoughts3_1.5B-Q5_K_M.gguf) | Q5_K_M | 1.125 GB | large, very low quality loss - recommended |
| [OpenThoughts3_1.5B-Q6_K.gguf](https://huggingface.co/tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF/blob/main/OpenThoughts3_1.5B-Q6_K.gguf) | Q6_K | 1.273 GB | very large, extremely low quality loss |
| [OpenThoughts3_1.5B-Q8_0.gguf](https://huggingface.co/tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF/blob/main/OpenThoughts3_1.5B-Q8_0.gguf) | Q8_0 | 1.647 GB | very large, extremely low quality loss - not recommended |
## Downloading instruction
### Command line
Firstly, install Huggingface Client
```shell
pip install -U "huggingface_hub[cli]"
```
Then, downoad the individual model file the a local directory
```shell
huggingface-cli download tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF --include "OpenThoughts3_1.5B-Q2_K.gguf" --local-dir MY_LOCAL_DIR
```
If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
```shell
huggingface-cli download tensorblock/mlfoundations-dev_OpenThoughts3_1.5B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```
|