GGUF
Image-Text-to-Text
qwen3_6
token-efficient
efficient-thinking
llama-cpp
gguf-my-repo
unsloth
qwen
qwen3_5
Instructions to use gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-GGUF", filename="mmproj-BF16.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 gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-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 gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-GGUF:BF16 # Run inference directly in the terminal: llama cli -hf gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-GGUF:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-GGUF:BF16 # Run inference directly in the terminal: llama cli -hf gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-GGUF:BF16
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 gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-GGUF:BF16 # Run inference directly in the terminal: ./llama-cli -hf gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-GGUF:BF16
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 gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-GGUF:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-GGUF:BF16
Use Docker
docker model run hf.co/gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-GGUF:BF16
- LM Studio
- Jan
- Ollama
How to use gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-GGUF with Ollama:
ollama run hf.co/gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-GGUF:BF16
- Unsloth Studio
How to use gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-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 gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-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 gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-GGUF with Docker Model Runner:
docker model run hf.co/gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-GGUF:BF16
- Lemonade
How to use gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-GGUF:BF16
Run and chat with the model
lemonade run user.ThinkingCap-Qwen3.6-27B-Q6_K-GGUF-BF16
List all available models
lemonade list
Update README.md
Browse files
README.md
CHANGED
|
@@ -7,6 +7,9 @@ tags:
|
|
| 7 |
- efficient-thinking
|
| 8 |
- llama-cpp
|
| 9 |
- gguf-my-repo
|
|
|
|
|
|
|
|
|
|
| 10 |
---
|
| 11 |
|
| 12 |
# gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-GGUF
|
|
|
|
| 7 |
- efficient-thinking
|
| 8 |
- llama-cpp
|
| 9 |
- gguf-my-repo
|
| 10 |
+
- unsloth
|
| 11 |
+
- qwen
|
| 12 |
+
- qwen3_5
|
| 13 |
---
|
| 14 |
|
| 15 |
# gopi87/ThinkingCap-Qwen3.6-27B-Q6_K-GGUF
|