Upload TinyToolUse Calculator model

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+license: mit
+base_model: Qwen/Qwen2-0.5B
+tags:
+- tool-use
+- function-calling
+- calculator
+- tiny-tool-use
+- bagel-labs
+- fine-tuned
+language:
+- en
+pipeline_tag: text-generation
+library_name: transformers
+---
+
+# TinyToolUse-Qwen2-0.5B-Calculator
+
+A fine-tuned version of Qwen/Qwen2-0.5B trained for calculator tool usage using the [Tiny Tool Use](https://github.com/bagel-org/bagel-RL) library.
+
+## Model Description
+
+This model has been fine-tuned to understand and execute calculator tool calls. It can perform mathematical calculations by generating appropriate tool call syntax.
+
+- **Base Model**: Qwen/Qwen2-0.5B
+- **Training Method**: Supervised Fine-Tuning (SFT)
+- **Training Library**: Tiny Tool Use
+- **Tool**: Calculator (mathematical expressions)
+- **Parameters**: 500M
+- **Architecture**: 24 layers, 896 hidden dimensions
+
+## Training Details
+
+- **Training Data**: 4 custom calculator examples
+- **Training Steps**: 3 steps, 1 epoch
+- **Training Time**: ~8.5 seconds
+- **Hardware**: CPU training (RTX 4060 available but CUDA compatibility issues)
+- **Precision**: float32
+
+## Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+# Load model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained("your-username/TinyToolUse-Qwen2-0.5B-Calculator")
+model = AutoModelForCausalLM.from_pretrained("your-username/TinyToolUse-Qwen2-0.5B-Calculator")
+
+# Example usage
+prompt = "Human: What is 15 + 27?\nAssistant:"
+inputs = tokenizer(prompt, return_tensors="pt")
+
+with torch.no_grad():
+    outputs = model.generate(
+        inputs.input_ids,
+        max_new_tokens=100,
+        temperature=0.7,
+        do_sample=True,
+        pad_token_id=tokenizer.eos_token_id
+    )
+
+response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(response)
+```
+
+## Expected Output Format
+
+The model should generate responses in the format:
+```
+tool_code: print(calculator(expression='15 + 27'))
+```
+
+## Tool Definition
+
+The model was trained with this calculator tool definition:
+
+```json
+{
+  "name": "calculator",
+  "description": "Perform mathematical calculations",
+  "type": "function",
+  "parameters": {
+    "type": "object",
+    "properties": {
+      "expression": {
+        "type": "string",
+        "description": "Mathematical expression to evaluate"
+      }
+    },
+    "required": ["expression"]
+  }
+}
+```
+
+## Training Examples
+
+The model was trained on these examples:
+- "What is 2 + 2?" → `tool_code: print(calculator(expression='2 + 2'))`
+- "Calculate 10 * 5" → `tool_code: print(calculator(expression='10 * 5'))`
+- "What is 100 / 25?" → `tool_code: print(calculator(expression='100 / 25'))`
+- "Find the value of 3 to the power of 4." → `tool_code: print(calculator(expression='3 ** 4'))`
+
+## Limitations
+
+- Small training dataset (4 examples)
+- CPU-only training due to CUDA compatibility issues
+- Limited to calculator tool only
+- May require additional fine-tuning for production use
+
+## Framework
+
+This model was trained using the [Tiny Tool Use](https://github.com/bagel-org/bagel-RL) library, which provides:
+- Multiple training methods (SFT, DPO, Teacher Mode)
+- Flexible data generation strategies
+- Integration with Berkeley Function-Calling Leaderboard
+- Support for various LLM architectures
+
+## Citation
+
+```bibtex
+@misc{tinytooluse2024,
+  title={Tiny Tool Use: Training Open-Source LLMs for Tool Usage},
+  author={Bagel Labs},
+  year={2024},
+  url={https://github.com/bagel-org/bagel-RL}
+}
+```
+
+## License
+
+MIT License - see the [LICENSE](LICENSE) file for details.

added_tokens.json

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+{
+  "<|endoftext|>": 151643,
+  "<|im_end|>": 151645,
+  "<|im_start|>": 151644,
+  "[/RESULT]": 151649,
+  "[/TOOL_CALL]": 151647,
+  "[RESULT]": 151648,
+  "[TOOL_CALL]": 151646
+}

config.json

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+{
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "hidden_act": "silu",
+  "hidden_size": 896,
+  "initializer_range": 0.02,
+  "intermediate_size": 4864,
+  "layer_types": [
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+    "full_attention",
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+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 131072,
+  "max_window_layers": 24,
+  "model_type": "qwen2",
+  "num_attention_heads": 14,
+  "num_hidden_layers": 24,
+  "num_key_value_heads": 2,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.53.1",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151650
+}

generation_config.json

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+{
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "max_new_tokens": 2048,
+  "transformers_version": "4.53.1"
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9240ca07d4de4d80ec1416a429c03244023fc69ca19cd157014357824aea6016
+size 1975138448

model_card.json

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+{
+  "license": "mit",
+  "base_model": "Qwen/Qwen2-0.5B",
+  "tags": [
+    "tool-use",
+    "function-calling",
+    "calculator",
+    "tiny-tool-use",
+    "bagel-labs",
+    "fine-tuned"
+  ],
+  "language": [
+    "en"
+  ],
+  "pipeline_tag": "text-generation",
+  "library_name": "transformers"
+}

requirements.txt

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+torch>=2.0.0
+transformers>=4.30.0
+tokenizers>=0.13.0

special_tokens_map.json

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+      "normalized": false,
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+    "single_word": false
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+  "pad_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

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+oid sha256:1613481d58c0c98f4a249f3d850f893901460e06569015261ee26b1ea8f0ea69
+size 11419014

tokenizer_config.json

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+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|endoftext|>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "model_max_length": 32768,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}