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README.md

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+---
+license: apache-2.0
+language:
+- en
+tags:
+- automatic-speech-recognition
+- hf-asr-leaderboard
+- whisper
+- qwen
+- llama-cpp
+- gguf-my-repo
+pipeline_tag: automatic-speech-recognition
+base_model: bosonai/higgs-audio-v3-8b-stt-v2
+model-index:
+- name: higgs-audio-v3-8b-stt-v2
+  results:
+  - task:
+      type: automatic-speech-recognition
+      name: Automatic Speech Recognition
+    dataset:
+      name: AMI (Meetings test)
+      type: edinburghcstr/ami
+      config: ihm
+      split: test
+      args:
+        language: en
+    metrics:
+    - type: wer
+      value: 10.14
+      name: Test WER
+  - task:
+      type: automatic-speech-recognition
+      name: Automatic Speech Recognition
+    dataset:
+      name: Earnings-22
+      type: revdotcom/earnings22
+      split: test
+      args:
+        language: en
+    metrics:
+    - type: wer
+      value: 8.73
+      name: Test WER
+  - task:
+      type: automatic-speech-recognition
+      name: Automatic Speech Recognition
+    dataset:
+      name: GigaSpeech
+      type: speechcolab/gigaspeech
+      split: test
+      args:
+        language: en
+    metrics:
+    - type: wer
+      value: 8.47
+      name: Test WER
+  - task:
+      type: automatic-speech-recognition
+      name: Automatic Speech Recognition
+    dataset:
+      name: LibriSpeech (clean)
+      type: librispeech_asr
+      config: clean
+      split: test
+      args:
+        language: en
+    metrics:
+    - type: wer
+      value: 1.25
+      name: Test WER
+  - task:
+      type: automatic-speech-recognition
+      name: Automatic Speech Recognition
+    dataset:
+      name: LibriSpeech (other)
+      type: librispeech_asr
+      config: other
+      split: test
+      args:
+        language: en
+    metrics:
+    - type: wer
+      value: 2.38
+      name: Test WER
+  - task:
+      type: automatic-speech-recognition
+      name: Automatic Speech Recognition
+    dataset:
+      name: SPGI Speech
+      type: kensho/spgispeech
+      config: test
+      split: test
+      args:
+        language: en
+    metrics:
+    - type: wer
+      value: 3.6
+      name: Test WER
+  - task:
+      type: automatic-speech-recognition
+      name: Automatic Speech Recognition
+    dataset:
+      name: tedlium-v3
+      type: LIUM/tedlium
+      config: release1
+      split: test
+      args:
+        language: en
+    metrics:
+    - type: wer
+      value: 3.09
+      name: Test WER
+  - task:
+      type: automatic-speech-recognition
+      name: Automatic Speech Recognition
+    dataset:
+      name: Vox Populi
+      type: facebook/voxpopuli
+      config: en
+      split: test
+      args:
+        language: en
+    metrics:
+    - type: wer
+      value: 5.92
+      name: Test WER
+---
+
+# nopesadly/higgs-audio-v3-8b-stt-v2-Q4_K_M-GGUF
+This model was converted to GGUF format from [`bosonai/higgs-audio-v3-8b-stt-v2`](https://huggingface.co/bosonai/higgs-audio-v3-8b-stt-v2) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
+Refer to the [original model card](https://huggingface.co/bosonai/higgs-audio-v3-8b-stt-v2) for more details on the model.
+
+## Use with llama.cpp
+Install llama.cpp through brew (works on Mac and Linux)
+
+```bash
+brew install llama.cpp
+
+```
+Invoke the llama.cpp server or the CLI.
+
+### CLI:
+```bash
+llama-cli --hf-repo nopesadly/higgs-audio-v3-8b-stt-v2-Q4_K_M-GGUF --hf-file higgs-audio-v3-8b-stt-v2-q4_k_m.gguf -p "The meaning to life and the universe is"
+```
+
+### Server:
+```bash
+llama-server --hf-repo nopesadly/higgs-audio-v3-8b-stt-v2-Q4_K_M-GGUF --hf-file higgs-audio-v3-8b-stt-v2-q4_k_m.gguf -c 2048
+```
+
+Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
+
+Step 1: Clone llama.cpp from GitHub.
+```
+git clone https://github.com/ggerganov/llama.cpp
+```
+
+Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
+```
+cd llama.cpp && LLAMA_CURL=1 make
+```
+
+Step 3: Run inference through the main binary.
+```
+./llama-cli --hf-repo nopesadly/higgs-audio-v3-8b-stt-v2-Q4_K_M-GGUF --hf-file higgs-audio-v3-8b-stt-v2-q4_k_m.gguf -p "The meaning to life and the universe is"
+```
+or
+```
+./llama-server --hf-repo nopesadly/higgs-audio-v3-8b-stt-v2-Q4_K_M-GGUF --hf-file higgs-audio-v3-8b-stt-v2-q4_k_m.gguf -c 2048
+```