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+whisper-base-q4_0.gguf filter=lfs diff=lfs merge=lfs -text
+whisper-base-q4_1.gguf filter=lfs diff=lfs merge=lfs -text
+whisper-base-q8_0.gguf filter=lfs diff=lfs merge=lfs -text
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+whisper.cpp/whisper-base-q5_0.gguf filter=lfs diff=lfs merge=lfs -text
+whisper.cpp/whisper-base-q5_1.gguf filter=lfs diff=lfs merge=lfs -text
+whisper.cpp/whisper-base-q5_k.gguf filter=lfs diff=lfs merge=lfs -text
+whisper.cpp/whisper-base-q6_k.gguf filter=lfs diff=lfs merge=lfs -text
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LICENSE

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+MIT License
+
+Copyright (c) 2022 OpenAI
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

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+---
+license: mit
+language:
+- multilingual
+- en
+- ru
+tags:
+- whisper
+- gguf
+- quantized
+- speech-recognition
+- rust
+base_model:
+- openai/whisper-base
+---
+
+# WHISPER-BASE - GGUF Quantized Models
+
+Quantized versions of [openai/whisper-base](https://huggingface.co/openai/whisper-base) in GGUF format.
+
+## Directory Structure
+
+```
+base/
+├── whisper-base-q*.gguf       # Candle-compatible GGUF models (root)
+├── config.json                # Model configuration for Candle
+├── tokenizer.json             # Tokenizer for Candle
+└── whisper.cpp/               # whisper.cpp-compatible models
+    └── whisper-base-q*.gguf
+
+```
+
+### Format Compatibility
+
+- **Root directory** (`whisper-base-*.gguf`): Use with **Candle** (Rust ML framework)
+  - Tensor names include `model.` prefix (e.g., `model.encoder.conv1.weight`)
+  - Compatible with Neurolang application
+  - Requires `config-base.json` and `tokenizer-base.json`
+  
+- **whisper.cpp/** directory: Use with **whisper.cpp** (C++ implementation)
+  - Tensor names without `model.` prefix (e.g., `encoder.conv1.weight`)
+  - Compatible with whisper.cpp CLI tools
+  - Both directories contain `.gguf` files, not `.bin` files
+
+## Available Formats
+
+| Format |  Quality | Use Case |
+|--------| ---------|----------|
+| q2_k |   Smallest | Extreme compression |
+| q3_k |  Small | Mobile devices |
+| q4_0 |  Good | Legacy compatibility |
+| q4_k |  Good | **Recommended for production** |
+| q4_1 | Good+ | Legacy with bias |
+| q5_0 |  Very Good | Legacy compatibility |
+| q5_k |  Very Good | High quality |
+| q5_1 |  Very Good+ | Legacy with bias |
+| q6_k |   Excellent | Near-lossless |
+| q8_0 |   Excellent | Minimal loss, benchmarking |
+
+## Usage
+
+### With Candle (Rust)
+
+> For this model, you need to modify the example code in candle. To try whisper in candle faster and easier, it's better to use the tiny model → https://huggingface.co/oxide-lab/whisper-tiny-GGUF
+
+**Command line example:**
+```bash
+# Run Candle Whisper with local quantized model
+cargo run --example whisper --release -- \
+  --features symphonia \
+  --quantized \
+  --model base \
+  --model-id oxide-lab/whisper-base-GGUF \
+```
+
+### With whisper.cpp (C++)
+
+```bash
+# Use models from whisper.cpp/ subdirectory
+./whisper.cpp/build/bin/whisper-cli \
+  --model models/openai/base/whisper.cpp/whisper-base-q4_k.gguf \
+  --file audio.wav
+```
+
+### Recommended Format
+
+For most use cases, we recommend **q4_k** format as it provides the best balance of:
+- Size reduction (~65% smaller)
+- Quality (minimal degradation)
+- Speed (faster inference than higher quantizations)
+
+## Quantization Details
+
+- **Source Model**: [openai/whisper-base](https://huggingface.co/openai/whisper-base)
+- **Quantization Methods**:
+  - **Candle GGUF** (root directory): Python-based quantization via `convert_whisper_to_gguf.py`
+    - Adds `model.` prefix to tensor names for Candle compatibility
+  - **whisper.cpp GGML** (whisper.cpp/ subdirectory): whisper-quantize tool
+    - Uses original tensor names without prefix
+- **Format**: GGUF (GGML Universal Format) for both directories
+- **Total Formats**: 10 quantization levels (q2_k through q8_0)
+
+## License
+
+Same as the original Whisper model (MIT License).
+
+## Citation
+
+```bibtex
+@misc{radford2022whisper,
+  doi = {10.48550/ARXIV.2212.04356},
+  url = {https://arxiv.org/abs/2212.04356},
+  author = {Radford, Alec and Kim, Jong Wook and Xu, Tao and Brockman, Greg and McLeavey, Christine and Sutskever, Ilya},
+  title = {Robust Speech Recognition via Large-Scale Weak Supervision},
+  publisher = {arXiv},
+  year = {2022},
+  copyright = {arXiv.org perpetual, non-exclusive license}
+}
+```

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