Instructions to use qwp4w3hyb/Starling-LM-7B-beta-iMat-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use qwp4w3hyb/Starling-LM-7B-beta-iMat-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("qwp4w3hyb/Starling-LM-7B-beta-iMat-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use qwp4w3hyb/Starling-LM-7B-beta-iMat-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 qwp4w3hyb/Starling-LM-7B-beta-iMat-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf qwp4w3hyb/Starling-LM-7B-beta-iMat-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf qwp4w3hyb/Starling-LM-7B-beta-iMat-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf qwp4w3hyb/Starling-LM-7B-beta-iMat-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 qwp4w3hyb/Starling-LM-7B-beta-iMat-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf qwp4w3hyb/Starling-LM-7B-beta-iMat-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 qwp4w3hyb/Starling-LM-7B-beta-iMat-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf qwp4w3hyb/Starling-LM-7B-beta-iMat-GGUF:Q4_K_M

Use Docker

docker model run hf.co/qwp4w3hyb/Starling-LM-7B-beta-iMat-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use qwp4w3hyb/Starling-LM-7B-beta-iMat-GGUF with Ollama:
```
ollama run hf.co/qwp4w3hyb/Starling-LM-7B-beta-iMat-GGUF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use qwp4w3hyb/Starling-LM-7B-beta-iMat-GGUF with Docker Model Runner:
```
docker model run hf.co/qwp4w3hyb/Starling-LM-7B-beta-iMat-GGUF:Q4_K_M
```

Lemonade

How to use qwp4w3hyb/Starling-LM-7B-beta-iMat-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull qwp4w3hyb/Starling-LM-7B-beta-iMat-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Starling-LM-7B-beta-iMat-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

qwp4w3hyb commited on Mar 28, 2024

Commit

7ce04f8

verified ·

1 Parent(s): 12b62bc

Update README.md

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@@ -1,3 +1,29 @@
 ---
 license: apache-2.0
 ---

 ---
+base_model: Nexusflow/Starling-LM-7B-beta
+datasets:
+- berkeley-nest/Nectar
+language:
+- en
+library_name: transformers
+tags:
+- starling
+- reward model
+- RLHF
+- RLAIF
+model-index:
+- name: Nexusflow/Starling-LM-7B-beta-iMat-GGUF
+  results: []
 license: apache-2.0
 ---
+# Starling-LM-7B-beta-iMat-GGUF
+Source Model: [Nexusflow/Starling-LM-7B-beta](https://huggingface.co/Nexusflow/Starling-LM-7B-beta)
+Quantized with [llama.cpp](https://github.com/ggerganov/llama.cpp) commit [46acb3676718b983157058aecf729a2064fc7d34](https://github.com/ggerganov/llama.cpp/commit/46acb3676718b983157058aecf729a2064fc7d34)
+Imatrix was generated from the f16 gguf via this command:
+./imatrix -c 512 -m $out_path/$base_quant_name -f $llama_cpp_path/groups_merged.txt -o $out_path/imat-f16-gmerged.dat
+Using the dataset from [here](https://github.com/ggerganov/llama.cpp/discussions/5263#discussioncomment-8395384)