Instructions to use mradermacher/Crow-9B-it-i1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mradermacher/Crow-9B-it-i1-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mradermacher/Crow-9B-it-i1-GGUF", dtype="auto") - llama-cpp-python
How to use mradermacher/Crow-9B-it-i1-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="mradermacher/Crow-9B-it-i1-GGUF", filename="Crow-9B-it.i1-IQ1_M.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 mradermacher/Crow-9B-it-i1-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf mradermacher/Crow-9B-it-i1-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf mradermacher/Crow-9B-it-i1-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf mradermacher/Crow-9B-it-i1-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf mradermacher/Crow-9B-it-i1-GGUF: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 mradermacher/Crow-9B-it-i1-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf mradermacher/Crow-9B-it-i1-GGUF: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 mradermacher/Crow-9B-it-i1-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf mradermacher/Crow-9B-it-i1-GGUF:Q4_K_M
Use Docker
docker model run hf.co/mradermacher/Crow-9B-it-i1-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use mradermacher/Crow-9B-it-i1-GGUF with Ollama:
ollama run hf.co/mradermacher/Crow-9B-it-i1-GGUF:Q4_K_M
- Unsloth Studio
How to use mradermacher/Crow-9B-it-i1-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 mradermacher/Crow-9B-it-i1-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 mradermacher/Crow-9B-it-i1-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for mradermacher/Crow-9B-it-i1-GGUF to start chatting
- Docker Model Runner
How to use mradermacher/Crow-9B-it-i1-GGUF with Docker Model Runner:
docker model run hf.co/mradermacher/Crow-9B-it-i1-GGUF:Q4_K_M
- Lemonade
How to use mradermacher/Crow-9B-it-i1-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mradermacher/Crow-9B-it-i1-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Crow-9B-it-i1-GGUF-Q4_K_M
List all available models
lemonade list
auto-patch README.md
Browse files
README.md
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| Link | Type | Size/GB | Notes |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own quants) |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-IQ1_M.gguf) | i1-IQ1_M | 2.6 | mostly desperate |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-IQ2_M.gguf) | i1-IQ2_M | 3.5 | |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-Q2_K_S.gguf) | i1-Q2_K_S | 3.7 | very low quality |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 3.9 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-Q2_K.gguf) | i1-Q2_K | 3.9 | IQ3_XXS probably better |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-Q3_K_S.gguf) | i1-Q3_K_S | 4.4 | IQ3_XS probably better |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-IQ3_M.gguf) | i1-IQ3_M | 4.6 | |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-Q3_K_M.gguf) | i1-Q3_K_M | 4.9 | IQ3_S probably better |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-IQ4_XS.gguf) | i1-IQ4_XS | 5.3 | |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-IQ4_NL.gguf) | i1-IQ4_NL | 5.5 | prefer IQ4_XS |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-Q4_K_S.gguf) | i1-Q4_K_S | 5.6 | optimal size/speed/quality |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-Q4_K_M.gguf) | i1-Q4_K_M | 5.9 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-Q6_K.gguf) | i1-Q6_K | 7.7 | practically like static Q6_K |
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Here is a handy graph by ikawrakow comparing some lower-quality quant
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| Link | Type | Size/GB | Notes |
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|:-----|:-----|--------:|:------|
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own quants) |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-IQ1_S.gguf) | i1-IQ1_S | 2.5 | for the desperate |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-IQ1_M.gguf) | i1-IQ1_M | 2.6 | mostly desperate |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.9 | |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-IQ2_XS.gguf) | i1-IQ2_XS | 3.2 | |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-IQ2_S.gguf) | i1-IQ2_S | 3.3 | |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-IQ2_M.gguf) | i1-IQ2_M | 3.5 | |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-Q2_K_S.gguf) | i1-Q2_K_S | 3.7 | very low quality |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 3.9 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-Q2_K.gguf) | i1-Q2_K | 3.9 | IQ3_XXS probably better |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-IQ3_XS.gguf) | i1-IQ3_XS | 4.2 | |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-IQ3_S.gguf) | i1-IQ3_S | 4.4 | beats Q3_K* |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-Q3_K_S.gguf) | i1-Q3_K_S | 4.4 | IQ3_XS probably better |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-IQ3_M.gguf) | i1-IQ3_M | 4.6 | |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-Q3_K_M.gguf) | i1-Q3_K_M | 4.9 | IQ3_S probably better |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-Q3_K_L.gguf) | i1-Q3_K_L | 5.2 | IQ3_M probably better |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-IQ4_XS.gguf) | i1-IQ4_XS | 5.3 | |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-IQ4_NL.gguf) | i1-IQ4_NL | 5.5 | prefer IQ4_XS |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-Q4_0.gguf) | i1-Q4_0 | 5.6 | fast, low quality |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-Q4_K_S.gguf) | i1-Q4_K_S | 5.6 | optimal size/speed/quality |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-Q4_K_M.gguf) | i1-Q4_K_M | 5.9 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-Q4_1.gguf) | i1-Q4_1 | 6.1 | |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-Q5_K_S.gguf) | i1-Q5_K_S | 6.6 | |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-Q5_K_M.gguf) | i1-Q5_K_M | 6.7 | |
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| [GGUF](https://huggingface.co/mradermacher/Crow-9B-it-i1-GGUF/resolve/main/Crow-9B-it.i1-Q6_K.gguf) | i1-Q6_K | 7.7 | practically like static Q6_K |
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Here is a handy graph by ikawrakow comparing some lower-quality quant
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