Instructions to use SandLogicTechnologies/translategemma-4b-it-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SandLogicTechnologies/translategemma-4b-it-GGUF with Transformers:

# Use a pipeline as a high-level helper
# Warning: Pipeline type "translation" is no longer supported in transformers v5.
# You must load the model directly (see below) or downgrade to v4.x with:
# 'pip install "transformers<5.0.0'
from transformers import pipeline

pipe = pipeline("translation", model="SandLogicTechnologies/translategemma-4b-it-GGUF")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("SandLogicTechnologies/translategemma-4b-it-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use SandLogicTechnologies/translategemma-4b-it-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 SandLogicTechnologies/translategemma-4b-it-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf SandLogicTechnologies/translategemma-4b-it-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 SandLogicTechnologies/translategemma-4b-it-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf SandLogicTechnologies/translategemma-4b-it-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 SandLogicTechnologies/translategemma-4b-it-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf SandLogicTechnologies/translategemma-4b-it-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 SandLogicTechnologies/translategemma-4b-it-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf SandLogicTechnologies/translategemma-4b-it-GGUF:Q4_K_M

Use Docker

docker model run hf.co/SandLogicTechnologies/translategemma-4b-it-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use SandLogicTechnologies/translategemma-4b-it-GGUF with Ollama:
```
ollama run hf.co/SandLogicTechnologies/translategemma-4b-it-GGUF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use SandLogicTechnologies/translategemma-4b-it-GGUF with Docker Model Runner:
```
docker model run hf.co/SandLogicTechnologies/translategemma-4b-it-GGUF:Q4_K_M
```

Lemonade

How to use SandLogicTechnologies/translategemma-4b-it-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull SandLogicTechnologies/translategemma-4b-it-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.translategemma-4b-it-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

SandLogicTechnologies commited on Jan 19

Commit

cd39c30

verified ·

1 Parent(s): f82d9bd

Update README.md

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@@ -1,14 +1,18 @@
 ---
 license: gemma
-language:
 - multilingual
--base_model: google/translategemma-4b-it
 tags:
 - Translation
 - Multilingual
 - Instruction-Tuned
 - Natural Language Processing
 - Text Generation
 ---
 # Quantized TranslateGemma-4B-IT Model

 ---
 license: gemma
+language:
 - multilingual
+'-base_model': google/translategemma-4b-it
 tags:
 - Translation
 - Multilingual
 - Instruction-Tuned
 - Natural Language Processing
 - Text Generation
+base_model:
+- google/translategemma-4b-it
+pipeline_tag: translation
+library_name: transformers
 ---
 # Quantized TranslateGemma-4B-IT Model