refactor: enhance model unloading and memory management for improved GPU efficiency

refactor: enable CPU offload and adjust model loading for improved performance

refactor: disable KV cache to prevent quality degradation after multiple requests

refactor: enable 8-bit quantization and adjust device map for improved model loading diagnostics

refactor: disable 8-bit quantization and set device map to CPU when GPU is unavailable

refactor: enable 8-bit quantization for improved memory efficiency in Transformers model loading

refactor: disable 8-bit quantization and CPU offload for optimized model loading on T4 GPUs

fix: improve error handling during model loading and fallback for quantization failures

refactor: remove unused model configurations and streamline model creation logic

refactor: remove runtime installation of llama-cpp-python, now pre-installed via requirements.txt

feat: Add main backup and simplified service implementations with API endpoints

fix: streamline CPU offload handling in model loading for better memory management

feat: add CPU offload support for Transformers model to optimize memory usage

feat: add Transformers model support with GPU optimization and 8-bit quantization

feat: add model size and polish support to model info

fix: use prebuilt CUDA wheel for llama-cpp-python

fix: use python3.10 instead of python3.9 for ubuntu 22.04

fix: defer model downloads to first request

refactor: defer llama-cpp-python install to runtime

fix: use symlinks instead of update-alternatives for python

fix: correct Dockerfile syntax for llama-cpp-python fallback

refactor: consolidate to single unified Dockerfile with GPU support

config: add GPU Dockerfile to README frontmatter

feat: add GPU-enabled Dockerfile.gpu for HF Spaces CUDA support

fix: graceful fallback for llama-cpp-python installation on HF Spaces

fix: enable CUDA compilation for llama-cpp-python

perf: defer llama-cpp-python build to runtime startup

fix: remove invalid chown command from Dockerfile

feat: enable GPU acceleration for Bielik GGUF models

update Dockerfile and README.md to replace Qwen2.5-3B and Gemma-2-2B with Bielik-1.5B-GGUF; adjust model loading instructions in the API documentation

update HuggingFaceInferenceAPI comment for clarity; change huggingface_hub version to minimum required

refine GBNF grammar for car advertisement; ensure compact JSON output and improve gap-item structure

add model management methods to ModelRegistry; include model listing, loading, and unloading functionalities

add HuggingFace Inference API model; implement async initialization and text generation with caching

add GBNF grammar for car advertisement gap filling; update LlamaCppModel to support loading grammar from file

add GBNF grammar utilities for structured LLM output; integrate grammar in model generation

enhance infill processing to handle custom messages; return cleaned output directly when provided

update llama-cpp-python installation to version 0.3.16 for improved compatibility

install llama-cpp-python at runtime to avoid build issues in HuggingFace Spaces; update requirements.txt to reflect this change

update LlamaCppModel initialization parameters and enable verbose logging for model loading; update llama-cpp-python requirement

enhance error handling in LlamaCppModel initialization; include full traceback on failure

add get_info method to return model details for /models endpoint

add debug logging for batch infill and model generation processes; update bielik model configuration

increase context size and improve message handling in LlamaCppModel

update requirements with libmetadata

dockerfile fix

fixing naming for bielik gguf

improved-index-url

fix-docker-error-for-gguf

adding-bielik-gguf