ermiaazarkhalili
/

Qwen2.5-14B-Instruct_Function_Calling_xLAM

@@ -1,199 +1,147 @@
 ---
 library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
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 ---
+license: cc-by-nc-4.0
+tags:
+- text-generation
+- qwen2.5-14b-instruct
+- function-calling
+- finetuned-model
+- trl
+- lora
+- Salesforce/xlam-function-calling-60k
+datasets:
+- Salesforce/xlam-function-calling-60k
+base_model: Qwen/Qwen2.5-14B-Instruct
 library_name: transformers
+languages:
+- en
+pipeline_tag: text-generation
 ---
+# Qwen2.5-14B-Instruct Fine-tuned on xLAM
+## Overview
+This is a fine-tuned version of the Qwen2.5-14B-Instruct model. The model was trained using Hugging Face's TRL library on the xLAM dataset for function calling capabilities.
 ## Model Details
+- **Developed by:** ermiaazarkhalili
+- **License:** cc-by-nc-4.0
+- **languages:** en
+- **Finetuned from model:** Qwen/Qwen2.5-14B-Instruct
+- **Model size:** Qwen2.5-14B-Instruct parameters
+- **Vocab size:** 152,064 tokens
+- **Max sequence length:** 2,048 tokens
+- **Tensor type:** BF16
+- **Pad token:** `<|im_end|>` (ID: 151645)
+## Training Information
+The model was fine-tuned using the following configuration:
+### Training Libraries
+- **Hugging Face TRL Library** for advanced training techniques
+- **LoRA (Low-Rank Adaptation)** for parameter-efficient training
+- **4-bit quantization** for memory efficiency
+### Training Parameters
+- **Learning Rate:** 0.0001
+- **Batch Size:** 4
+- **Gradient Accumulation Steps:** 8
+- **Max Training Steps:** 1,000
+- **Warmup Ratio:** 0.1
+- **Max Sequence Length:** 2,048
+- **Output Directory:** ./Qwen2_5_14B_Instruct_xLAM
+### LoRA Configuration
+- **LoRA Rank (r):** 16
+- **LoRA Alpha:** 32
+- **Target Modules:** Query and Value projections
+- **LoRA Dropout:** 0.1
+## Usage
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+# Load model and tokenizer
+model = AutoModelForCausalLM.from_pretrained(
+    "ermiaazarkhalili/Qwen2.5-14B-Instruct_Function_Calling_xLAM",
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+    trust_remote_code=True
+)
+tokenizer = AutoTokenizer.from_pretrained(
+    "ermiaazarkhalili/Qwen2.5-14B-Instruct_Function_Calling_xLAM",
+    trust_remote_code=True
+)
+text= "<user>Check if the numbers 8 and 1233 are powers of two.</user>\n\n<tools>"
+# Tokenize and generate
+inputs = tokenizer(text, return_tensors="pt").to(model.device)
+outputs = model.generate(
+    **inputs,
+    max_new_tokens=512,
+    temperature=0.7,
+    do_sample=True,
+    pad_token_id=tokenizer.pad_token_id,
+    eos_token_id=tokenizer.eos_token_id
+)
+# Decode response
+response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+generated_text = response[len(text):].strip()
+print(generated_text)
+```
+## Dataset
+The model was trained on the **xLAM** dataset.
+## Model Performance
+This fine-tuned model demonstrates improved capabilities in:
+- **Function Detection:** Identifying when to call functions
+- **Parameter Extraction:** Extracting correct parameters from user queries
+- **Output Formatting:** Generating properly structured function calls
+- **Tool Integration:** Working with external APIs and tools
+## Credits
+This model was developed by [ermiaazarkhalili](https://huggingface.co/ermiaazarkhalili) and leverages the capabilities of:
+- **Qwen2.5-14B-Instruct** base model
+- **Hugging Face TRL** for advanced fine-tuning techniques
+- **LoRA** for parameter-efficient adaptation
+## Contact
+For any inquiries or support, please reach out to the developer at [ermiaazarkhalili](https://huggingface.co/ermiaazarkhalili).
+## Acknowledgments
+We would like to thank the creators of:
+- **Qwen2.5-14B-Instruct** for the excellent base model
+- **Hugging Face** for the TRL library and infrastructure
+- **xLAM** dataset contributors
+- **LoRA** researchers for parameter-efficient fine-tuning methods
+## Citation
+If you use this model, please cite:
+```bibtex
+@misc{ermiaazarkhalili_Qwen2.5-14B-Instruct_Function_Calling_xLAM,
+author = {ermiaazarkhalili},
+title = { Fine-tuning  Qwen2.5-14B-Instruct on xLAM for Function Calling},
+year = {2025},
+publisher = {Hugging Face},
+howpublished = {\url{https://huggingface.co/ermiaazarkhalili/Qwen2.5-14B-Instruct_Function_Calling_xLAM}}
+}
+```