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Model: ermiaazarkhalili/Granite-4.1-3B-Function-Calling-xLAM-Unsloth
Source: Original Platform

.gitattributes

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README.md

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+---
+license: apache-2.0
+language:
+  - en
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+  - unsloth
+  - granite
+  - sft
+  - fine-tuned
+  - trl
+  - lora
+  - qlora
+  - text-generation
+  - function-calling
+  - conversational
+base_model: ibm-granite/granite-4.1-3b
+datasets:
+  - Salesforce/xlam-function-calling-60k
+model-index:
+  - name: Granite-4.1-3B-Function-Calling-xLAM-Unsloth
+    results: []
+---
+
+# Granite-4.1-3B-Function-Calling-xLAM-Unsloth
+
+This model is a fine-tuned version of [Granite 4.1-3B](https://huggingface.co/ibm-granite/granite-4.1-3b) optimized for **function calling** using [Unsloth](https://github.com/unslothai/unsloth) for **2x faster training** and **60% less VRAM**.
+
+Trained on the [Salesforce/xlam-function-calling-60k](https://huggingface.co/datasets/Salesforce/xlam-function-calling-60k) dataset, which contains 60,000 function calling examples with queries, tool definitions, and structured answers.
+
+## Overview
+
+| Property | Value |
+|----------|-------|
+| **Developed by** | [ermiaazarkhalili](https://huggingface.co/ermiaazarkhalili) |
+| **License** | APACHE-2.0 |
+| **Language** | English |
+| **Base Model** | [Granite 4.1-3B](https://huggingface.co/ibm-granite/granite-4.1-3b) |
+| **Model Size** | 3B parameters |
+| **Training Framework** | [Unsloth](https://github.com/unslothai/unsloth) + [TRL](https://github.com/huggingface/trl) |
+| **Training Method** | SFT with QLoRA (4-bit) |
+| **Context Length** | 2,048 tokens |
+| **GGUF Available** | [Granite-4.1-3B-Function-Calling-xLAM-Unsloth-GGUF](https://huggingface.co/ermiaazarkhalili/Granite-4.1-3B-Function-Calling-xLAM-Unsloth-GGUF) |
+
+## Training Configuration
+
+### SFT + LoRA Settings
+
+| Parameter | Value |
+|-----------|-------|
+| Unsloth Class | `FastLanguageModel` |
+| Chat Template | built-in Granite 4.1 |
+| Learning Rate | 2e-4 |
+| Batch Size | 2 per device |
+| Gradient Accumulation | 4 steps |
+| Effective Batch Size | 8 |
+| Max Steps | 1 epoch (full dataset) |
+| Optimizer | AdamW 8-bit |
+| LR Scheduler | Linear |
+| Warmup Steps | 5 |
+| Precision | Auto (BF16/FP16) |
+| Gradient Checkpointing | Enabled (Unsloth optimized) |
+| Seed | 3407 |
+
+### LoRA Configuration
+
+| Parameter | Value |
+|-----------|-------|
+| LoRA Rank (r) | 16 |
+| LoRA Alpha | 16 |
+| LoRA Dropout | 0 |
+| Quantization | 4-bit QLoRA |
+| Target Modules | q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj |
+
+### Dataset
+
+| Property | Value |
+|----------|-------|
+| Dataset | [xLAM Function Calling 60K](https://huggingface.co/datasets/Salesforce/xlam-function-calling-60k) |
+| Training Samples | 60,000 |
+| Format | XML-tagged: `<query>`, `<tools>`, `<answers>` |
+
+### Hardware
+
+| Property | Value |
+|----------|-------|
+| GPU | NVIDIA H100 80GB HBM3 (MIG 3g.40gb slice) |
+| Cluster | DRAC Fir (Compute Canada) |
+| Execution | [Papermill](https://github.com/nteract/papermill) on SLURM |
+
+### Training Outcome
+
+| Metric | Value |
+|--------|-------|
+| SLURM Job ID | `38330898` |
+| Runtime | 2h 47m 29s (10049s) |
+| Final Training Loss | 0.2242 |
+| Peak VRAM | 10.09 GB |
+| GPU | H100 80GB HBM3 (MIG 3g.40gb) |
+
+## Usage
+
+### Quick Start (Transformers)
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model_id = "ermiaazarkhalili/Granite-4.1-3B-Function-Calling-xLAM-Unsloth"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+
+messages = [
+    {"role": "user", "content": "Check if the numbers 8 and 1233 are powers of two."}
+]
+
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer(text, return_tensors="pt").to(model.device)
+
+outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.7, do_sample=True)
+response = tokenizer.decode(outputs[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True)
+print(response)
+```
+
+### Using with Unsloth (Fastest)
+
+```python
+from unsloth import FastLanguageModel
+
+model, tokenizer = FastLanguageModel.from_pretrained(
+    "ermiaazarkhalili/Granite-4.1-3B-Function-Calling-xLAM-Unsloth",
+    max_seq_length=2048,
+    load_in_4bit=True,
+)
+
+```
+
+### 4-bit Quantized Inference
+
+```python
+from transformers import AutoModelForCausalLM, BitsAndBytesConfig
+import torch
+
+quantization_config = BitsAndBytesConfig(
+    load_in_4bit=True,
+    bnb_4bit_compute_dtype=torch.bfloat16,
+    bnb_4bit_use_double_quant=True,
+    bnb_4bit_quant_type="nf4",
+)
+
+model = AutoModelForCausalLM.from_pretrained(
+    "ermiaazarkhalili/Granite-4.1-3B-Function-Calling-xLAM-Unsloth",
+    quantization_config=quantization_config,
+    device_map="auto",
+)
+```
+
+## GGUF Versions
+
+Quantized GGUF versions for CPU and edge inference are available at:
+**[Granite-4.1-3B-Function-Calling-xLAM-Unsloth-GGUF](https://huggingface.co/ermiaazarkhalili/Granite-4.1-3B-Function-Calling-xLAM-Unsloth-GGUF)**
+
+| Format | Description |
+|--------|-------------|
+| `Q4_K_M` | Recommended — good balance of quality and size |
+| `Q5_K_M` | Higher quality, slightly larger |
+| `Q8_0` | Near-lossless, largest GGUF size |
+
+### Using with Ollama
+
+```bash
+ollama pull hf.co/ermiaazarkhalili/Granite-4.1-3B-Function-Calling-xLAM-Unsloth-GGUF:Q4_K_M
+ollama run hf.co/ermiaazarkhalili/Granite-4.1-3B-Function-Calling-xLAM-Unsloth-GGUF:Q4_K_M "Check if the numbers 8 and 1233 are powers of two."
+```
+
+### Using with llama.cpp
+
+```bash
+./llama-cli -m Granite-4.1-3B-Function-Calling-xLAM-Unsloth-Q4_K_M.gguf -p "Check if the numbers 8 and 1233 are powers of two." -n 512
+```
+
+## Limitations
+
+- **Language**: Primarily trained on English data
+- **Knowledge Cutoff**: Limited to base model's training data cutoff
+- **Hallucinations**: May generate plausible-sounding but incorrect information
+- **Context Length**: Fine-tuned with 2,048 token context window
+- **Safety**: Not extensively safety-tuned; use with appropriate guardrails
+
+## Training Framework Versions
+
+| Package | Version |
+|---------|---------|
+| Unsloth | 2026.4.4 |
+| TRL | 0.24.0 |
+| Transformers | 5.5.0 |
+| PyTorch | 2.9.0 |
+| Datasets | 4.3.0 |
+| PEFT | 0.18.1 |
+| BitsAndBytes | 0.49.2 |
+
+## Citation
+
+```bibtex
+@misc{ermiaazarkhalili_granite_41_3b_function_calling_xlam_unsloth,
+    author = {ermiaazarkhalili},
+    title = {Granite-4.1-3B-Function-Calling-xLAM-Unsloth: Fine-tuned Granite 4.1-3B with Unsloth},
+    year = {2026},
+    publisher = {Hugging Face},
+    howpublished = {\url{https://huggingface.co/ermiaazarkhalili/Granite-4.1-3B-Function-Calling-xLAM-Unsloth}}
+}
+```
+
+## Acknowledgments
+
+- [Unsloth](https://github.com/unslothai/unsloth) for 2x faster fine-tuning
+- Base model developers (ibm-granite)
+- [Hugging Face TRL Team](https://github.com/huggingface/trl) for the training library
+- [Salesforce xLAM](https://huggingface.co/datasets/Salesforce/xlam-function-calling-60k) for the function calling dataset
+- [Compute Canada / DRAC](https://alliancecan.ca/) for HPC resources

chat_template.jinja

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+{%- set tools_system_message_prefix = 'You are a helpful assistant with access to the following tools. You may call one or more tools to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>'  %}
+{%- set tools_system_message_suffix = '\n</tools>\n\nFor each tool 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>. If a tool does not exist in the provided list of tools, notify the user that you do not have the ability to fulfill the request.' %}
+{%- set documents_system_message_prefix = 'You are a helpful assistant with access to the following documents. You may use one or more documents to assist with the user query.\n\nYou are given a list of documents within <documents></documents> XML tags:\n<documents>' %}
+{%- set documents_system_message_suffix = '\n</documents>\n\nWrite the response to the user\'s input by strictly aligning with the facts in the provided documents. If the information needed to answer the question is not available in the documents, inform the user that the question cannot be answered based on the available data.' %}
+{%- if available_tools is defined and available_tools %}
+    {%- set tools = available_tools %}
+{%- endif %}
+{%- set ns = namespace(tools_system_message=tools_system_message_prefix,
+                       documents_system_message=documents_system_message_prefix,
+                       system_message=''
+                       ) %}
+{%- if tools %}
+    {%- for tool in tools %}
+        {%- set ns.tools_system_message = ns.tools_system_message + '\n' + (tool | tojson) %}
+    {%- endfor %}
+    {%- set ns.tools_system_message = ns.tools_system_message + tools_system_message_suffix %}
+{%- else %}
+    {%- set ns.tools_system_message = '' %}
+{%- endif %}
+{%- if documents %}
+    {%- for document in documents %}
+        {%- set ns.documents_system_message = ns.documents_system_message + '\n' + (document | tojson) %}
+    {%- endfor %}
+    {%- set ns.documents_system_message = ns.documents_system_message + documents_system_message_suffix %}
+{%- else %}
+    {%- set ns.documents_system_message = '' %}
+{%- endif %}
+{%- if messages[0].role == 'system' %}
+    {%- if messages[0].content is string %}
+        {%- set ns.system_message = messages[0].content %}
+    {%- elif messages[0].content is iterable %}
+        {%- for entry in messages[0].content %}
+            {%- if entry.type== 'text' %}
+                {%- if ns.system_message != '' %}
+                    {%- set ns.system_message = ns.system_message + '\n' %}
+                {%- endif %}
+                {%- set ns.system_message = ns.system_message + entry.text %}
+            {%- endif %}
+        {%- endfor %}
+    {%- endif %}
+    {%- if tools and documents %}
+        {%- set ns.system_message = ns.system_message + '\n\n' +  ns.tools_system_message + '\n\n' + ns.documents_system_message %}
+    {%- elif tools %}
+        {%- set ns.system_message = ns.system_message + '\n\n' + ns.tools_system_message %}
+    {%- elif documents %}
+        {%- set ns.system_message = ns.system_message + '\n\n' + ns.documents_system_message %}
+    {%- endif %}
+{%- else %}
+    {%- if tools and documents %}
+        {%- set ns.system_message = ns.tools_system_message + '\n\n' + ns.documents_system_message  %}
+    {%- elif tools %}
+        {%- set ns.system_message = ns.tools_system_message %}
+    {%- elif documents %}
+        {%- set ns.system_message = ns.documents_system_message %}
+    {%- endif %}
+{%- endif %}
+{%- if ns.system_message %}
+    {{- '<|start_of_role|>system<|end_of_role|>' + ns.system_message + '<|end_of_text|>\n' }}
+{%- endif %}
+{%- for message in messages %}
+    {%- set content = namespace(val='') %}
+    {%- if message.content is string %}
+        {%- set content.val = message.content %}
+    {%- else %}
+        {%- if message.content is iterable %}
+            {%- for entry in message.content %}
+                {%- if entry.type== 'text' %}
+                    {%- if content.val != '' %}
+                        {%- set content.val = content.val + '\n' %}
+                    {%- endif %}
+                    {%- set content.val = content.val + entry.text %}
+                {%- endif %}
+            {%- endfor %}
+        {%- endif %}
+    {%- endif %}
+    {%- if (message.role == 'user') or (message.role == 'system' and not loop.first) %}
+        {{- '<|start_of_role|>' + message.role + '<|end_of_role|>' + content.val + '<|end_of_text|>\n' }}
+    {%- elif message.role == 'assistant' %}
+        {{- '<|start_of_role|>' + message.role + '<|end_of_role|>' + content.val }}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and content.val) or (not loop.first) %}
+                    {{- '\n' }}
+                {%- endif %}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<tool_call>\n{"name": "' }}
+                {{- tool_call.name }}
+                {{- '", "arguments": ' }}
+                {%- if tool_call.arguments is string %}
+                    {{- tool_call.arguments }}
+                {%- else %}
+                    {{- tool_call.arguments | tojson }}
+                {%- endif %}
+                {{- '}\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|end_of_text|>\n' }}
+    {%- elif message.role == 'tool' %}
+        {%- if loop.first or (messages[loop.index0 - 1].role != 'tool') %}
+            {{- '<|start_of_role|>user<|end_of_role|>' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content.val }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != 'tool') %}
+            {{- '<|end_of_text|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|start_of_role|>assistant<|end_of_role|>' }}
+{%- endif %}

config.json

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+{
+    "architectures": [
+        "GraniteForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "attention_multiplier": 0.015625,
+    "bos_token_id": 100257,
+    "torch_dtype": "bfloat16",
+    "embedding_multiplier": 12.0,
+    "eos_token_id": 100257,
+    "hidden_act": "silu",
+    "hidden_size": 2560,
+    "initializer_range": 0.1,
+    "intermediate_size": 8192,
+    "logits_scaling": 10.0,
+    "max_position_embeddings": 131072,
+    "mlp_bias": false,
+    "model_name": "ibm-granite/granite-4.1-3b",
+    "model_type": "granite",
+    "num_attention_heads": 40,
+    "num_hidden_layers": 40,
+    "num_key_value_heads": 8,
+    "pad_token_id": 100256,
+    "residual_multiplier": 0.22,
+    "rms_norm_eps": 1e-05,
+    "rope_parameters": {
+        "rope_theta": 10000000,
+        "rope_type": "default"
+    },
+    "tie_word_embeddings": true,
+    "unsloth_version": "2026.4.6",
+    "use_cache": false,
+    "vocab_size": 100352
+}

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