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Model: ajayk007/Qwen2.5-Coder-1.5B-Shellsmith
Source: Original Platform

.gitattributes

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README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen2.5-Coder-1.5B-Instruct
+tags:
+  - mlx
+  - lora
+  - text-generation
+  - shell
+  - command-line
+  - code
+language:
+  - en
+pipeline_tag: text-generation
+library_name: mlx
+---
+
+# Qwen2.5-Coder-1.5B-Shellsmith
+
+A small, fast model that turns **plain-English instructions into a single shell
+command** for macOS/Linux. LoRA fine-tune of
+[`Qwen/Qwen2.5-Coder-1.5B-Instruct`](https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B-Instruct),
+trained and quantized end-to-end on an Apple Silicon Mac with
+[MLX](https://github.com/ml-explore/mlx).
+
+> "list files by size, biggest first" → `ls -lS`
+> "find files larger than 100 megabytes" → `find . -type f -size +100M`
+> "create a gzip tar archive of src named src.tar.gz" → `tar -czf src.tar.gz src`
+
+## Results
+
+Evaluated on a held-out test split the model never saw during training.
+Metrics are structural (no command execution) and conservative — see the
+[eval rubric](https://github.com/saiajay1/shellsmith/blob/main/eval/rubric.md).
+
+| Model | exact-match | command-match | flag-F1 |
+| --- | :---: | :---: | :---: |
+| Base (Qwen2.5-Coder-1.5B-Instruct) | 71% | 83.9% | 89.2% |
+| **This model (LoRA)** | **100%** | **100%** | **100%** |
+
+*command-match = correct program **and** option-flag F1 ≥ 0.8.*
+
+> **What the 100% means (and doesn't):** the test split holds out unseen
+> *phrasings*, but the underlying task distribution (84 canonical tasks) overlaps
+> with training. So this measures reliable **in-distribution generalization across
+> wording** — the model consistently emits the canonical, idiomatic command
+> (`git add -A`, `ls -lS`, `git log --oneline -5`) where the base model drifts to
+> looser variants (`git add .`, `ls -lh | sort -rh`, `git log -5`). It is **not**
+> evidence of generalization to entirely novel tasks; broadening the task set is
+> the obvious next step.
+
+## Usage
+
+### MLX (Apple Silicon)
+
+```bash
+pip install mlx-lm
+mlx_lm.generate --model ajayk007/Qwen2.5-Coder-1.5B-Shellsmith \
+  --prompt "compress the logs folder into logs.tar.gz"
+```
+
+```python
+from mlx_lm import load, generate
+model, tok = load("ajayk007/Qwen2.5-Coder-1.5B-Shellsmith")
+messages = [
+    {"role": "system", "content": "You are a shell command generator for macOS/Linux. "
+     "Given a task in plain English, reply with a single safe shell command. "
+     "Output only the command on one line, no explanation, no markdown."},
+    {"role": "user", "content": "find all python files modified today"},
+]
+prompt = tok.apply_chat_template(messages, add_generation_prompt=True, tokenize=False)
+print(generate(model, tok, prompt=prompt, max_tokens=64))
+```
+
+### GGUF (llama.cpp / Ollama / LM Studio)
+
+A `shellsmith-1.5b-f16.gguf` file is included in this repo for use with llama.cpp-based runtimes.
+
+## Prompt format
+
+Uses the Qwen chat template with the system prompt shown above. Keep the system
+prompt for best results.
+
+## Training
+
+- **Method:** LoRA (rank 16), 16 layers, 400 iterations, batch size 4, lr 1e-4
+- **Hardware:** Apple M5 Pro (48 GB), MLX
+- **Data:** [`ajayk007/shellsmith-commands`](https://huggingface.co/datasets/ajayk007/shellsmith-commands) —
+  curated (instruction, command) pairs with paraphrase augmentation, 80/10/10 split.
+
+## Limitations & safety
+
+- Generates commands across common categories (files, find/grep, archives, git,
+  processes, networking). Outside this scope it falls back to base behavior.
+- **Always read a generated command before running it.** It can produce
+  destructive commands (`rm`, `kill`, `chmod`) if you ask for them. There is no
+  sandbox or confirmation step.
+- Single-command only; it does not write multi-step scripts.
+
+## Related
+Part of a series of focused "English → developer DSL" fine-tunes:
+- [Qwen2.5-Coder-7B-Querysmith](https://huggingface.co/ajayk007/Qwen2.5-Coder-7B-Querysmith) — schema-grounded text-to-SQL.
+
+## License
+
+Apache-2.0, inheriting from the base model.

chat_template.jinja

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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- messages[0]['content'] }}
+    {%- else %}
+        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
+    {%- endif %}
+    {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
+    {%- else %}
+        {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role }}
+        {%- if message.content %}
+            {{- '\n' + message.content }}
+        {%- endif %}
+        {%- for tool_call in message.tool_calls %}
+            {%- if tool_call.function is defined %}
+                {%- set tool_call = tool_call.function %}
+            {%- endif %}
+            {{- '\n<tool_call>\n{"name": "' }}
+            {{- tool_call.name }}
+            {{- '", "arguments": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- '}\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

config.json

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+{
+    "architectures": [
+        "Qwen2ForCausalLM"
+    ],
+    "attention_dropout": 0.0,
+    "bos_token_id": 151643,
+    "eos_token_id": [
+        151645,
+        151643
+    ],
+    "hidden_act": "silu",
+    "hidden_size": 1536,
+    "initializer_range": 0.02,
+    "intermediate_size": 8960,
+    "max_position_embeddings": 32768,
+    "max_window_layers": 28,
+    "model_type": "qwen2",
+    "num_attention_heads": 12,
+    "num_hidden_layers": 28,
+    "num_key_value_heads": 2,
+    "quantization": {
+        "group_size": 64,
+        "bits": 4,
+        "mode": "affine"
+    },
+    "quantization_config": {
+        "group_size": 64,
+        "bits": 4,
+        "mode": "affine"
+    },
+    "rms_norm_eps": 1e-06,
+    "rope_theta": 1000000.0,
+    "sliding_window": 32768,
+    "tie_word_embeddings": true,
+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.44.0",
+    "use_cache": true,
+    "use_sliding_window": false,
+    "vocab_size": 151936
+}

generation_config.json

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+{
+  "bos_token_id": 151643,
+  "pad_token_id": 151643,
+  "do_sample": true,
+  "eos_token_id": [
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+    151643
+  ],
+  "repetition_penalty": 1.1,
+  "temperature": 0.7,
+  "top_p": 0.8,
+  "top_k": 20,
+  "transformers_version": "4.44.0"
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