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Model: marksverdhai/asr-to-bash-gguf
Source: Original Platform

README.md

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+---
+license: apache-2.0
+base_model: google/functiongemma-270m-it
+tags:
+  - function-calling
+  - asr
+  - bash
+  - voice-commands
+  - gemma
+datasets:
+  - custom
+language:
+  - en
+pipeline_tag: text-generation
+---
+
+# ASR-to-Bash (GGUF)
+
+Fine-tuned FunctionGemma (270M) model that converts ASR (speech-to-text) transcriptions into executable bash commands.
+
+## Usage
+
+```python
+# For llama.cpp / Ollama usage
+# llama-cli -m asr-to-bash-q4_k_m.gguf -p 'Convert: list all files'
+
+# Or with Python:
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("marksverdhai/asr-to-bash")
+tokenizer = AutoTokenizer.from_pretrained("marksverdhai/asr-to-bash")
+
+messages = [
+    {"role": "system", "content": "You are a helpful assistant that converts spoken commands into bash commands."},
+    {"role": "user", "content": "Convert this spoken command to bash: list all files including hidden ones"}
+]
+
+inputs = tokenizer.apply_chat_template(messages, return_tensors="pt")
+outputs = model.generate(inputs, max_new_tokens=50)
+print(tokenizer.decode(outputs[0]))
+# Output: ls -la
+```
+
+## Examples
+
+| ASR Transcription | Bash Command |
+|------------------|--------------|
+| "list all files" | `ls -la` |
+| "git status" | `git status` |
+| "change directory to home" | `cd ~` |
+| "kill process one two three four" | `kill 1234` |
+| "show running containers" | `docker ps` |
+
+## Training
+
+Fine-tuned using Unsloth with LoRA on a custom dataset of ~100 ASR transcription to bash command pairs.
+
+- Base model: `google/functiongemma-270m-it`
+- LoRA rank: 16
+- Training epochs: 3