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Model: dipta007/GanitLLM-0.6B_CGRPO Source: Original Platform
2026-04-22 02:50:58 +08:00
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--- a/README.md
+++ b/README.md
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+---
+library_name: transformers
+license: apache-2.0
+base_model: Qwen/Qwen3-0.6B
+pipeline_tag: text-generation
+language:
+  - bn
+  - en
+tags:
+  - math
+  - bengali
+  - reasoning
+  - grpo
+  - curriculum-learning
+datasets:
+  - dipta007/Ganit
+---
+
+# GanitLLM-0.6B_CGRPO
+
+<p align="center">
+  <a href="https://arxiv.org/abs/2601.06767">
+    <img src="https://img.shields.io/badge/%F0%9F%94%A5_Accepted_at-ACL_2026_(Findings)_%F0%9F%94%A5-b12a00?style=for-the-badge&labelColor=ffb300" alt="Accepted at ACL 2026 (Findings)">
+  </a>
+</p>
+
+[![ACL 2026 (Findings)](https://img.shields.io/badge/ACL%202026-Findings-blue)](https://arxiv.org/abs/2601.06767)
+[![Paper](https://img.shields.io/badge/arXiv-2601.06767-red)](https://arxiv.org/abs/2601.06767)
+[![Project Page](https://img.shields.io/badge/Project-Page-green)](https://dipta007.github.io/GanitLLM/)
+[![Dataset](https://img.shields.io/badge/HuggingFace-Dataset-yellow)](https://huggingface.co/datasets/dipta007/Ganit)
+[![Models](https://img.shields.io/badge/HuggingFace-Models-orange)](https://huggingface.co/collections/dipta007/ganitllm)
+[![GitHub](https://img.shields.io/badge/GitHub-Code-blue)](https://github.com/dipta007/GanitLLM)
+
+## Highlights
+
+**GanitLLM-0.6B_CGRPO** is a Bengali mathematical reasoning model trained with Curriculum-GRPO directly on the base model (without SFT). This variant shows limited improvement at this scale. Key results:
+
+- **+8.8 accuracy** on Bn-MGSM benchmark (8.4 → 17.2)
+- **+23.0 accuracy** on Bn-MSVAMP benchmark (12.2 → 35.2)
+- **11.67% Bengali reasoning** (similar to base model)
+- **34.9% fewer tokens** in generated solutions (1265 → 824 words)
+
+> **Note**: This model shows limited gains at the 0.6B scale. For better performance, use [GanitLLM-0.6B_SFT_CGRPO](https://huggingface.co/dipta007/GanitLLM-0.6B_SFT_CGRPO) or consider larger models.
+
+## Model Overview
+
+| Property | Value |
+|----------|-------|
+| **Model Type** | Causal Language Model |
+| **Base Model** | Qwen/Qwen3-0.6B |
+| **Parameters** | 0.6B |
+| **Training** | Curriculum-GRPO (no SFT) |
+| **Context Length** | 4,096 tokens |
+| **Language** | Bengali, English |
+
+## Training Details
+
+This model was trained with a single-stage pipeline:
+
+1. **Curriculum-GRPO**: Reinforcement learning with difficulty-aware sampling directly on the base model using GANIT-RLVR (~7.3k examples)
+
+### Reward Functions
+- **Format Reward**: Validates `<think>` and `<answer>` tag structure
+- **Correctness Reward**: +2.0 for Bengali answer match, +1.0 for English match
+- **Bengali Reasoning Reward**: Ensures >80% Bengali text in reasoning
+
+## Quickstart
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "dipta007/GanitLLM-0.6B_CGRPO"
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype="auto",
+    device_map="auto"
+)
+
+problem = "একটি দোকানে ১২টি আপেল আছে। যদি ৫টি আপেল বিক্রি হয়, তাহলে কতটি আপেল বাকি থাকবে?"
+
+prompt = f"""A conversation takes place between the user and the assistant. The user asks a question, and the assistant solves the problem. Please reason step by step in Bengali, and put your final answer in the <answer> </answer> tags.
+
+Question: {problem}"""
+
+messages = [{"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=2048, temperature=0.7)
+output_ids = generated_ids[0][len(model_inputs.input_ids[0]):].tolist()
+response = tokenizer.decode(output_ids, skip_special_tokens=True)
+print(response)
+```
+
+### Using vLLM
+
+```bash
+vllm serve dipta007/GanitLLM-0.6B_CGRPO --max-model-len 4096
+```
+
+## Performance
+
+| Model | Bn-MGSM | Bn-MSVAMP | Avg. Words | Bengali % |
+|-------|---------|-----------|------------|-----------|
+| Qwen3-0.6B (base) | 8.40 | 12.20 | 1265 | 12.43% |
+| **GanitLLM-0.6B_CGRPO** | **17.20** | **35.20** | **824** | **11.67%** |
+
+## Related Models
+
+| Model | Parameters | Training | Link |
+|-------|------------|----------|------|
+| GanitLLM-4B_CGRPO | 4B | CGRPO | [Link](https://huggingface.co/dipta007/GanitLLM-4B_CGRPO) |
+| GanitLLM-1.7B_CGRPO | 1.7B | CGRPO | [Link](https://huggingface.co/dipta007/GanitLLM-1.7B_CGRPO) |
+| GanitLLM-0.6B_SFT_CGRPO | 0.6B | SFT + CGRPO | [Link](https://huggingface.co/dipta007/GanitLLM-0.6B_SFT_CGRPO) |
+| GanitLLM-0.6B_SFT_GRPO | 0.6B | SFT + GRPO | [Link](https://huggingface.co/dipta007/GanitLLM-0.6B_SFT_GRPO) |
+| **GanitLLM-0.6B_CGRPO** | 0.6B | CGRPO | [Link](https://huggingface.co/dipta007/GanitLLM-0.6B_CGRPO) |
+
+## Citation
+
+```bibtex
+@inproceedings{dipta2026ganitllm,
+  title={GanitLLM: Difficulty-Aware Bengali Mathematical Reasoning through Curriculum-GRPO},
+  author={Shubhashis Roy Dipta and Khairul Mahbub and Nadia Najjar},
+  booktitle={Findings of the Association for Computational Linguistics: ACL 2026},
+  year={2026},
+  eprint={2601.06767},
+  archivePrefix={arXiv},
+  primaryClass={cs.CL},
+  url={https://arxiv.org/abs/2601.06767},
+}
+```
+
+## License
+
+This model is released under the Apache 2.0 License.
--- a/added_tokens.json
+++ b/added_tokens.json
@@ -0,0 +1,28 @@
+{
+  "</think>": 151668,
+  "</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,
+  "<|quad_start|>": 151650,
+  "<|repo_name|>": 151663,
+  "<|video_pad|>": 151656,
+  "<|vision_end|>": 151653,
+  "<|vision_pad|>": 151654,
+  "<|vision_start|>": 151652
+}
--- a/chat_template.jinja
+++ b/chat_template.jinja
@@ -0,0 +1,99 @@
+{%- 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 %}
--- a/config.json
+++ b/config.json
@@ -0,0 +1,62 @@
+{
+  "architectures": [
+    "Qwen3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "torch_dtype": "bfloat16",
+  "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,
+  "transformers_version": "4.56.2",
+  "unsloth_fixed": true,
+  "unsloth_version": "2025.11.2",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}
--- a/merges.txt
+++ b/merges.txt
--- a/model.safetensors
+++ b/model.safetensors
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4547ed891a4d1e3949a0a8f828b6f4aa719df0b7b488fd4c417691583143a483
+size 1192135096
--- a/special_tokens_map.json
+++ b/special_tokens_map.json
@@ -0,0 +1,31 @@
+{
+  "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|>"
+  ],
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|vision_pad|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}
--- a/tokenizer.json
+++ b/tokenizer.json
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:132c0fb88b2070b782a69e8833d01ab987b1198ec606df151512d91820abb758
+size 11422822
--- a/tokenizer_config.json
+++ b/tokenizer_config.json
--- a/vocab.json
+++ b/vocab.json