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Model: prithivMLmods/Gliese-Query_Tool-0.6B
Source: Original Platform

.gitattributes

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README.md

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+---
+license: apache-2.0
+datasets:
+- Salesforce/xlam-function-calling-60k
+language:
+- en
+base_model:
+- Qwen/Qwen3-0.6B
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- trl
+- text-generation-inference
+- agent
+- tool_calling
+- fun()
+---
+
+![1](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/INHbIlmGb9oSeBfo6xt-Z.png)
+
+# **Gliese-Query_Tool-0.6B**
+
+> **Gliese-Query_Tool-0.6B** is a **function-calling and query-oriented reasoning model** fine-tuned from **Qwen3-0.6B** using **Salesforce/xlam-function-calling-60k**, designed for **tool orchestration**, **structured query resolution**, and **operation chaining** across diverse tasks.
+> It excels in **dynamic function execution**, **structured reasoning pipelines**, and **multi-tool decision workflows**, making it a powerful lightweight solution for **developers**, **tooling platforms**, and **automation systems**.
+
+> [!note]
+> GGUF: [https://huggingface.co/prithivMLmods/Gliese-Query_Tool-0.6B-GGUF](https://huggingface.co/prithivMLmods/Gliese-Query_Tool-0.6B-GGUF)
+
+---
+
+## **Key Features**
+
+1. **Function-Calling Focused Reasoning**
+   Fine-tuned with **Salesforce/xlam-function-calling-60k**, enabling precise function selection, argument formatting, and multi-step tool invocation in complex workflows.
+
+2. **Query-Oriented Workflow Design**
+   Built to parse, interpret, and resolve complex queries by selecting and chaining the most relevant functions or tools for the task.
+
+3. **Tool-Orchestration & Automation**
+   Handles structured tool calls, dynamic function dispatch, and hybrid reasoning to power intelligent automation, API orchestration, and backend agent pipelines.
+
+4. **Structured Multi-Format Output**
+   Outputs formatted responses in **JSON**, **YAML**, **Markdown**, and **structured argument objects** — ideal for direct integration into software pipelines and agentic systems.
+
+5. **Lightweight, Deployment-Ready Core**
+   Compact **0.6B parameter** size optimized for **edge deployments**, **on-device inference**, and **fast cold-starts** while maintaining strong reasoning and function-call accuracy.
+
+---
+
+## **sample inference.**
+
+```
+Solve 2**2
+```
+
+```py
+[{"name": "power", "description": "Calculates the power of a number with a specified exponent.",
+"parameters": {"number": {"description": "The base for which the power is calculated.", "type": "int"},
+"exponent": {"description": "The exponent to which the number should be raised.", "type": "int"}}}]
+```
+
+```
+solve for 'x' in the equation 2x + 5 = 11?
+```
+
+```py
+[{"name": "solving_equation", "description": "Solves a linear equation for a variable.",
+ "parameters": {"equation": {"description": "The equation to solve. The format is 'a*x + b = c'.
+For example, '5x + 2 = 10' or '3x - 7 = 1'.", "type": "str"}, "operation": {"description": "The operation (add, sub, etc.) to perform the solving.",
+"type": "str, optional"}, "variable": {"description": "The variable to solve for. Defaults to 'x' if not provided.", "default": "x"}}}]
+```
+
+```
+What is the volume of a sphere with a radius of 6 cm?
+```
+
+```py
+[{"name": "volume_of_sphere", "description": "Calculates the volume of a sphere given its radius using the formula (4/3)πr³.",
+"parameters": {"radius": {"description": "The radius of the sphere.", "type": "int"}}}]
+```
+
+```
+In an examination 80% of the candidates passed in Urdu and 85% in Hindi, while 75% passed in both . If 45 candidates failed in both. Then the total number of candidates was ?
+```
+
+```py
+[{"name": "passing_percentage", "description": "Calculates the passing percentage for an exam given the percentage of students who passed each subject, and the intersection percentage of passing subjects.",
+"parameters": {"subject1_percent": {"description": "Percentage of students who passed the first subject (e.g., 85% if Hindi).", "type": "int"},
+"subject2_percent": {"description": "Percentage of students who passed the second subject (e.g., 80% if Urdu).", "type": "int"}, "passed_both_percent": {"description": "Percentage of students who passed both subjects.", "type": "int"}}}]
+```
+
+## **Quickstart with Transformers**
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "prithivMLmods/Gliese-Query_Tool-0.6B"
+
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype="auto",
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+prompt = "Call the right function to fetch weather data for Paris and format the output as JSON."
+
+messages = [
+    {"role": "system", "content": "You are a query tool model skilled in function-calling, API orchestration, and structured query resolution."},
+    {"role": "user", "content": prompt}
+]
+
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
+)
+
+model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
+
+generated_ids = model.generate(
+    **model_inputs,
+    max_new_tokens=512
+)
+generated_ids = [
+    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+]
+
+response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+print(response)
+```
+
+## **Intended Use**
+
+* Intelligent function-calling and multi-step query solving
+* API orchestration, agent tool selection, and dynamic workflows
+* Structured data generation and backend reasoning integration
+* Lightweight agentic systems and on-device automation
+* Developer-focused query resolution and toolchain automation
+
+## **Limitations**
+
+* Focused on **function-calling and structured tasks** — not suited for open-ended dialogue or creative writing
+* Small model size means very complex reasoning chains may require external planning agents
+* Optimized for structured tool workflows — conversational tone and narrative depth are secondary
+* Long-context multi-tool planning beyond several steps may reduce reliability

added_tokens.json

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+{
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+  "</tool_call>": 151658,
+  "</tool_response>": 151666,
+  "<think>": 151667,
+  "<tool_call>": 151657,
+  "<tool_response>": 151665,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
+  "<|endoftext|>": 151643,
+  "<|file_sep|>": 151664,
+  "<|fim_middle|>": 151660,
+  "<|fim_pad|>": 151662,
+  "<|fim_prefix|>": 151659,
+  "<|fim_suffix|>": 151661,
+  "<|im_end|>": 151645,
+  "<|im_start|>": 151644,
+  "<|image_pad|>": 151655,
+  "<|object_ref_end|>": 151647,
+  "<|object_ref_start|>": 151646,
+  "<|quad_end|>": 151651,
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+  "<|vision_pad|>": 151654,
+  "<|vision_start|>": 151652
+}

chat_template.jinja

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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {{- messages[0].content + '\n\n' }}
+    {%- endif %}
+    {{- "# 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' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for forward_message in messages %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- set message = messages[index] %}
+    {%- set current_content = message.content if message.content is defined and message.content is not none else '' %}
+    {%- set tool_start = '<tool_response>' %}
+    {%- set tool_start_length = tool_start|length %}
+    {%- set start_of_message = current_content[:tool_start_length] %}
+    {%- set tool_end = '</tool_response>' %}
+    {%- set tool_end_length = tool_end|length %}
+    {%- set start_pos = (current_content|length) - tool_end_length %}
+    {%- if start_pos < 0 %}
+        {%- set start_pos = 0 %}
+    {%- endif %}
+    {%- set end_of_message = current_content[start_pos:] %}
+    {%- if ns.multi_step_tool and message.role == "user" and not(start_of_message == tool_start and end_of_message == tool_end) %}
+        {%- set ns.multi_step_tool = false %}
+        {%- set ns.last_query_index = index %}
+    {%- endif %}
+{%- endfor %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set m_content = message.content if message.content is defined and message.content is not none else '' %}
+        {%- set content = m_content %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is defined and message.reasoning_content is not none %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in m_content %}
+                {%- set content = (m_content.split('</think>')|last).lstrip('\n') %}
+                {%- set reasoning_content = (m_content.split('</think>')|first).rstrip('\n') %}
+                {%- set reasoning_content = (reasoning_content.split('<think>')|last).lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {%- if loop.last or (not loop.last and (not reasoning_content.strip() == '')) %}
+                {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
+            {%- else %}
+                {{- '<|im_start|>' + message.role + '\n' + content }}
+            {%- endif %}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and content) 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 %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.first 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' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- endif %}
+{%- endif %}

config.json

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+{
+  "architectures": [
+    "Qwen3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "eos_token_id": 151645,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_types": [
+    "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",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 40960,
+  "max_window_layers": 28,
+  "model_type": "qwen3",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 8,
+  "pad_token_id": 151654,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000,
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "torch_dtype": "float16",
+  "transformers_version": "4.55.4",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

configuration.json

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+{"framework": "pytorch", "task": "text-generation", "allow_remote": true}

merges.txt

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special_tokens_map.json

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+    "<|im_end|>",
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+    "lstrip": false,
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tokenizer_config.json

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+  "add_prefix_space": false,
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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151665": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151666": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151667": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151668": {
+      "content": "</think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "model_max_length": 40960,
+  "pad_token": "<|vision_pad|>",
+  "padding_side": "left",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}