from llama_cpp import Llama
llm = Llama(
model_path="translategemma-4b-it-LiteRT_Q4_K_M.gguf",
n_ctx=2048,
n_threads=4,
verbose=False,
)
response = llm.create_chat_completion(
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello! How can you help me today?"},
]
)
print(response["choices"][0]["message"]["content"])
Ollama
ollama run hf.co/DuoNeural/translategemma-4b-it-LiteRT
About the Conversion
Converted using
llama.cpp
GGUF pipeline with CUDA acceleration.
Source weights downloaded from HuggingFace, converted to F16 GGUF, then quantized to Q4_K_M.
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Runs of DuoNeural translategemma-4b-it-LiteRT on huggingface.co
52
Total runs
-9
24-hour runs
-19
3-day runs
-21
7-day runs
7
30-day runs
More Information About translategemma-4b-it-LiteRT huggingface.co Model
translategemma-4b-it-LiteRT huggingface.co
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DuoNeural translategemma-4b-it-LiteRT online free url in huggingface.co:
translategemma-4b-it-LiteRT is an open source model from GitHub that offers a free installation service, and any user can find translategemma-4b-it-LiteRT on GitHub to install. At the same time, huggingface.co provides the effect of translategemma-4b-it-LiteRT install, users can directly use translategemma-4b-it-LiteRT installed effect in huggingface.co for debugging and trial. It also supports api for free installation.
translategemma-4b-it-LiteRT install url in huggingface.co: