Instructions to use FoolDev/Thanatos-27B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FoolDev/Thanatos-27B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="FoolDev/Thanatos-27B") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("FoolDev/Thanatos-27B", dtype="auto") - llama-cpp-python
How to use FoolDev/Thanatos-27B with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="FoolDev/Thanatos-27B", filename="Thanatos-27B.Q4_K_M.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use FoolDev/Thanatos-27B with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf FoolDev/Thanatos-27B:Q4_K_M # Run inference directly in the terminal: llama-cli -hf FoolDev/Thanatos-27B:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf FoolDev/Thanatos-27B:Q4_K_M # Run inference directly in the terminal: llama-cli -hf FoolDev/Thanatos-27B: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 FoolDev/Thanatos-27B:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf FoolDev/Thanatos-27B: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 FoolDev/Thanatos-27B:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf FoolDev/Thanatos-27B:Q4_K_M
Use Docker
docker model run hf.co/FoolDev/Thanatos-27B:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use FoolDev/Thanatos-27B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "FoolDev/Thanatos-27B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FoolDev/Thanatos-27B", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/FoolDev/Thanatos-27B:Q4_K_M
- SGLang
How to use FoolDev/Thanatos-27B with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "FoolDev/Thanatos-27B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FoolDev/Thanatos-27B", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "FoolDev/Thanatos-27B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FoolDev/Thanatos-27B", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Ollama
How to use FoolDev/Thanatos-27B with Ollama:
ollama run hf.co/FoolDev/Thanatos-27B:Q4_K_M
- Unsloth Studio new
How to use FoolDev/Thanatos-27B 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 FoolDev/Thanatos-27B 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 FoolDev/Thanatos-27B to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for FoolDev/Thanatos-27B to start chatting
- Pi new
How to use FoolDev/Thanatos-27B with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf FoolDev/Thanatos-27B:Q4_K_M
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": "FoolDev/Thanatos-27B:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use FoolDev/Thanatos-27B with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf FoolDev/Thanatos-27B:Q4_K_M
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 FoolDev/Thanatos-27B:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use FoolDev/Thanatos-27B with Docker Model Runner:
docker model run hf.co/FoolDev/Thanatos-27B:Q4_K_M
- Lemonade
How to use FoolDev/Thanatos-27B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull FoolDev/Thanatos-27B:Q4_K_M
Run and chat with the model
lemonade run user.Thanatos-27B-Q4_K_M
List all available models
lemonade list
Rebadge bundle qwen35 -> qwen36 + doc the workaround
Browse filesRe-flip general.architecture in the bundled Q4_K_M GGUF to qwen36, the architecturally-honest label. Reverses f0d70ee (which itself reverted 2dbe526). No released llama.cpp / Ollama recognizes qwen36 yet (reconfirmed 2026-05-19 against llama.cpp 389ff61 + Ollama 0.24.0), so the bundle is unloadable on stock loaders until upstream adds the arch entry. README/Modelfile/CHANGELOG updated with the qwen36 -> qwen35 rebadge workaround (scripts/rename_arch.py is metadata-only, tensor data byte-identical). Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
- CHANGELOG.md +21 -0
- Modelfile +15 -4
- README.md +67 -42
- Thanatos-27B.Q4_K_M.gguf +1 -1
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389ff61 and Ollama 0.24.0), so `ollama run hf.co/FoolDev/Thanatos-27B`
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stays byte-identical; only metadata flips. Reverses prior commit
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`f0d70ee` which had restored qwen35 for compatibility; deliberate
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re-flip with eyes open about the breakage.
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loader matrix, Quick start Ollama block, and Modelfile preamble
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### Added
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`llama-server --mmproj` HTTP path (always built into stock llama.cpp,
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# Ollama uses when an mmproj is attached). Use llama.cpp directly for
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A personal sibling to [`FoolDev/Janus-35B`](https://huggingface.co/FoolDev/Janus-35B). Same teacher (Claude Opus 4.7), same dataset family, but built on the **dense** [Qwen/Qwen3.6-27B](https://huggingface.co/Qwen/Qwen3.6-27B) base instead of the 35B-A3B MoE. Smaller, easier to deploy, no expert-routing surprises.
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## TL;DR
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One-liner via Hugging Face (pulls a GGUF + this repo's root-level
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`Modelfile`):
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```bash
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For other quants (Q3_K_S ~12 GB, Q5_K_M ~20 GB, etc.), `make build
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three bridge files) for any quant:
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| `README.md` | This file |
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This repo ships a single GGUF to back the HF/Ollama "Use this model"
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```bash
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```bash
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## Quick start
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```bash
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# A. Pull straight from HF (uses the bundled Q4_K_M + root-level
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make build # Q4_K_M -> thanatos-27b
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make build QUANT=Q5_K_M # 20 GB higher quality
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### Local apps
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| App | How to load this model |
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|---|---|
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| **Ollama** | `ollama run hf.co/FoolDev/Thanatos-27B` (default Q4_K_M). Pulls the GGUF + the root-level `template` / `system` / `params` files in one step (HF's Ollama bridge ingests these three files; it does **not** read `Modelfile`). For other quants, `make build QUANT=Q3_K_S` downloads from unsloth and creates a local Ollama tag using the `Modelfile`, which is kept in sync with the bridge files. |
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| **LM Studio** | Search β `FoolDev/Thanatos-27B` β pick `Thanatos-27B.Q4_K_M.gguf`. Uses the GGUF's embedded jinja chat template (Qwen 3.6 ChatML); set the system prompt manually from the `SYSTEM` block in this repo's `Modelfile`. |
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| **Jan** | Hub β "Import from Hugging Face" β `FoolDev/Thanatos-27B`. Same template behavior as LM Studio. |
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| **llama.cpp** | `hf download FoolDev/Thanatos-27B Thanatos-27B.Q4_K_M.gguf --local-dir .` then `llama-server -m Thanatos-27B.Q4_K_M.gguf` (or `llama-cli`, `llama-mtmd-cli` for vision via the upstream `mmproj-F16.gguf`). |
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A personal sibling to [`FoolDev/Janus-35B`](https://huggingface.co/FoolDev/Janus-35B). Same teacher (Claude Opus 4.7), same dataset family, but built on the **dense** [Qwen/Qwen3.6-27B](https://huggingface.co/Qwen/Qwen3.6-27B) base instead of the 35B-A3B MoE. Smaller, easier to deploy, no expert-routing surprises.
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> β οΈ **Heads up β bundle is stamped `qwen36`.** As of 2026-05-19 the
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> bundled GGUF declares `general.architecture: 'qwen36'`, which no
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> released llama.cpp / Ollama recognizes yet. `ollama run
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> hf.co/FoolDev/Thanatos-27B` and `llama-server -m
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> Thanatos-27B.Q4_K_M.gguf` both fail today with `unknown model
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> architecture: 'qwen36'`. To load now, rebadge locally to `qwen35`:
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> see [Architecture](#architecture) for the one-liner. Once upstream
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> ships qwen36 the workaround disappears.
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## TL;DR
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One-liner via Hugging Face (pulls a GGUF + this repo's root-level
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`Modelfile`):
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```bash
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ollama run hf.co/FoolDev/Thanatos-27B # ~17 GB Q4_K_M, qwen36-stamped (see Heads-up above)
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```
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That command fails today with `unknown model architecture: 'qwen36'`
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until you rebadge locally β see [Architecture](#architecture).
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For other quants (Q3_K_S ~12 GB, Q5_K_M ~20 GB, etc.), `make build
|
| 88 |
+
QUANT=Q3_K_S` downloads from `unsloth/Qwen3.6-27B-GGUF` (which still
|
| 89 |
+
ships `qwen35`-stamped GGUFs) and creates the local Ollama tag.
|
| 90 |
+
See [Quick start](#quick-start) below.
|
| 91 |
|
| 92 |
Or build locally (uses this repo's `Modelfile`, kept in sync with the
|
| 93 |
three bridge files) for any quant:
|
|
|
|
| 144 |
| `README.md` | This file |
|
| 145 |
|
| 146 |
This repo ships a single GGUF to back the HF/Ollama "Use this model"
|
| 147 |
+
widget β `Thanatos-27B.Q4_K_M.gguf` (~17 GB, qwen36-stamped):
|
| 148 |
|
| 149 |
```bash
|
| 150 |
+
ollama run hf.co/FoolDev/Thanatos-27B # 17 GB Q4_K_M, qwen36 β fails today, see Heads-up above
|
| 151 |
```
|
| 152 |
|
| 153 |
+
For 16 GB GPUs / unified-memory laptops β and as a working-today
|
| 154 |
+
fallback while the bundle waits on upstream qwen36 support β
|
| 155 |
+
`make build QUANT=Q3_K_S` downloads the smaller ~12 GB Q3_K_S quant
|
| 156 |
+
from `unsloth/Qwen3.6-27B-GGUF` (qwen35-stamped, loads on every
|
| 157 |
+
current llama.cpp / Ollama build) and creates a local `thanatos-27b`
|
| 158 |
+
Ollama tag. Does not redistribute via this repo.
|
| 159 |
|
| 160 |
For other quants or local builds, pull from
|
| 161 |
[`unsloth/Qwen3.6-27B-GGUF`](https://huggingface.co/unsloth/Qwen3.6-27B-GGUF)
|
|
|
|
| 184 |
current loader compatibility.
|
| 185 |
- Multi-token prediction (MTP) head trained for speculative decoding
|
| 186 |
|
| 187 |
+
**The bundled GGUF declares `general.architecture: 'qwen36'`** β the
|
| 188 |
+
architecturally-honest stamp. Upstream `ggml-org/llama.cpp` and
|
| 189 |
+
`ollama/ollama` currently only register the hybrid SSM + attention
|
| 190 |
+
stack under `qwen35` / `qwen35moe`; no `qwen36` arch entry exists yet
|
| 191 |
+
(reconfirmed 2026-05-19 against llama.cpp 389ff61 and Ollama 0.24.0).
|
| 192 |
+
Consequence: **the bundle is unloadable on current stock loaders.**
|
| 193 |
+
`ollama run hf.co/FoolDev/Thanatos-27B` and `llama-server -m ...` both
|
| 194 |
+
fail with `error loading model architecture: unknown model
|
| 195 |
+
architecture: 'qwen36'` (Ollama 0.24 surfaces it as a 500 wrapping a
|
| 196 |
+
generic `unable to load model: <blob>` β check `journalctl --user -u
|
| 197 |
+
ollama` for the underlying line).
|
| 198 |
+
|
| 199 |
+
This is intentional. The bundle is the *correct* metadata; the
|
| 200 |
+
loaders are the lagging side. The flip is reversible until upstream
|
| 201 |
+
catches up β go the other direction locally with
|
| 202 |
+
`scripts/rename_arch.py` (metadata-only, tensors stay byte-identical):
|
| 203 |
|
| 204 |
```bash
|
| 205 |
+
# Get the bundle in a loadable state on today's llama.cpp / Ollama:
|
| 206 |
python3 scripts/rename_arch.py \
|
| 207 |
+
--from-arch qwen36 --to-arch qwen35 \
|
| 208 |
Thanatos-27B.Q4_K_M.gguf \
|
| 209 |
+
Thanatos-27B.Q4_K_M.qwen35.gguf
|
| 210 |
+
# Then either build a local Ollama tag (note absolute path β
|
| 211 |
+
# `ollama create` resolves a relative FROM against the Modelfile's
|
| 212 |
+
# directory, not your CWD):
|
| 213 |
+
echo "FROM $PWD/Thanatos-27B.Q4_K_M.qwen35.gguf" > /tmp/Modelfile.qwen35
|
| 214 |
+
ollama create thanatos-27b -f /tmp/Modelfile.qwen35
|
| 215 |
+
ollama run thanatos-27b hi
|
| 216 |
+
# β¦or point llama-server at the qwen35 file directly:
|
| 217 |
+
llama-server -m Thanatos-27B.Q4_K_M.qwen35.gguf -ngl 99 -c 8192
|
| 218 |
```
|
| 219 |
|
| 220 |
+
Once upstream adds the `qwen36` arch entry β patch landed in
|
| 221 |
+
`ggml-org/llama.cpp` and propagated into Ollama β the bundle works
|
| 222 |
+
as-is and the workaround above can be deleted.
|
|
|
|
|
|
|
|
|
|
|
|
|
| 223 |
|
| 224 |
## Quick start
|
| 225 |
|
|
|
|
| 229 |
|
| 230 |
```bash
|
| 231 |
# A. Pull straight from HF (uses the bundled Q4_K_M + root-level
|
| 232 |
+
# template / system / params files). Fails today with
|
| 233 |
+
# `unknown model architecture: 'qwen36'`; see Architecture for
|
| 234 |
+
# the qwen36 β qwen35 rebadge workaround.
|
| 235 |
+
ollama run hf.co/FoolDev/Thanatos-27B # 17 GB Q4_K_M, qwen36-stamped
|
| 236 |
|
| 237 |
+
# B. Build locally for a different quant (downloads qwen35-stamped
|
| 238 |
+
# GGUFs from unsloth β these load on today's llama.cpp / Ollama):
|
| 239 |
make build # Q4_K_M -> thanatos-27b
|
| 240 |
make build QUANT=Q3_K_S # 12 GB smaller quant
|
| 241 |
make build QUANT=Q5_K_M # 20 GB higher quality
|
|
|
|
| 261 |
|
| 262 |
### Local apps
|
| 263 |
|
| 264 |
+
The bundled `Thanatos-27B.Q4_K_M.gguf` is `qwen36`-stamped β every row
|
| 265 |
+
below assumes you've rebadged it to `qwen35` per
|
| 266 |
+
[Architecture](#architecture), or that you're pulling a `qwen35`-stamped
|
| 267 |
+
GGUF from `unsloth/Qwen3.6-27B-GGUF` instead. The "fails today with
|
| 268 |
+
`unknown model architecture: 'qwen36'`" caveat applies to every row
|
| 269 |
+
until that's done.
|
| 270 |
|
| 271 |
| App | How to load this model |
|
| 272 |
|---|---|
|
| 273 |
+
| **Ollama** | `ollama run hf.co/FoolDev/Thanatos-27B` (default Q4_K_M). Pulls the GGUF + the root-level `template` / `system` / `params` files in one step (HF's Ollama bridge ingests these three files; it does **not** read `Modelfile`). For other quants, or to bypass the qwen36 block today, `make build QUANT=Q3_K_S` downloads from unsloth (qwen35-stamped) and creates a local Ollama tag using the `Modelfile`, which is kept in sync with the bridge files. |
|
| 274 |
| **LM Studio** | Search β `FoolDev/Thanatos-27B` β pick `Thanatos-27B.Q4_K_M.gguf`. Uses the GGUF's embedded jinja chat template (Qwen 3.6 ChatML); set the system prompt manually from the `SYSTEM` block in this repo's `Modelfile`. |
|
| 275 |
| **Jan** | Hub β "Import from Hugging Face" β `FoolDev/Thanatos-27B`. Same template behavior as LM Studio. |
|
| 276 |
| **llama.cpp** | `hf download FoolDev/Thanatos-27B Thanatos-27B.Q4_K_M.gguf --local-dir .` then `llama-server -m Thanatos-27B.Q4_K_M.gguf` (or `llama-cli`, `llama-mtmd-cli` for vision via the upstream `mmproj-F16.gguf`). |
|
|
@@ -1,3 +1,3 @@
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