doing something
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@smlkw doing something, just my notes to keep updates
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knowledgator/gliner-bi-base-v1.0 + Helsinki-NLP/opus-mt-tc-big-zle-en in float16 precision

All test cases passing, but some entity types incorrectly detected
If you run MamayLM using llama-cpp:


podman run -v ./models:/models --device="nvidia.com/gpu=0" -p 8000:8000 ghcr.io/ggml-org/llama.cpp:server-cuda -m /models/MamayLM-Gemma-2-9B-IT-v0.1.Q4_K_S.gguf --port 8000 --host 0.0.0.0 -n 1024 --n-gpu-layers -1


Then it uses around 1480MiB on GPU

#nlp #llm
vLLM supports GGUF too - https://docs.vllm.ai/en/v0.9.0.1/features/quantization/gguf.html - but many model architectures are not supported at inference yet

#llm #ai #vllm
GitHub added hashes to binary files

Really useful thing
doing something
https://github.com/mozilla-ocho/llamafile/ #ai
Demo with gemma-3-1b-it-Q6_K model.

Generation is faster, pre-filling is enabled

#llm #ai
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