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Model: MihaiPopa-1/SmolLM2-135M-Math
Source: Original Platform

.gitattributes

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README.md

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+---
+datasets:
+- openai/gsm8k
+language:
+- en
+base_model:
+- HuggingFaceTB/SmolLM2-135M-Instruct
+pipeline_tag: text-generation
+tags:
+- safetensors
+- smollm
+- smollm2
+- math
+license: apache-2.0
+---
+# SmolLM2 Math
+## SmolLM2 but fine-tuned on math data!
+I just made a fine-tune of [SmolLM2 135M](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct) on the [GSM8K](https://huggingface.co/datasets/openai/gsm8k) dataset
+and it does improve math sometimes.
+## Evaluation Results
+| Metric | Value |
+| :----- | :--------: |
+| **Loss** | 1.284519 |
+| **Steps** | 2805 |
+## How to Use
+This code is by Gemini 3 Flash:
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "MihaiPopa-1/SmolLM2-135M-Math" # Replace with your repo path
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+prompt = "Question: If John has 5 apples and eats 2, then buys 4 more, how many does he have?\nAnswer:"
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=50)
+
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+## Comparision
+### First Question
+We both give the same question: "I have a number, 96. If the result is 24 and we divide it, what's the second part of the equation?"
+
+[SmolLM2 Math](https://huggingface.co/MihaiPopa-1/SmolLM2-135M-Math) gave:
+```
+Question: I have a number, 96. If the result is 24 and we divide it, what's the second part of the equation?
+Answer: The second part of the equation is 96 / 24 = 4.
+#### 4
+The answer is: 4
+```
+It correctly gave a answer.
+
+[SmolLM2 Base](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct) gave:
+```
+Question: I have a number, 96. If the result is 24 and we divide it, what's the second part of the equation?
+Answer:
+```
+It produced NOTHING!
+### Second Question
+Also, Gemini 2.5 Flash thought another question: "If 5 apples cost $2.50, how much does 1 apple cost?"
+
+So we put this question in both models.
+
+[SmolLM2 Math](https://huggingface.co/MihaiPopa-1/SmolLM2-135M-Math) gave:
+```
+Question: If 5 apples cost $2.50, how much does 1 apple cost?
+Answer: 1 apple = 100 apples
+2 apples = 100 * 2 = 200 apples
+1 apple = 100 * 2 = 200 apples
+#### 200
+The answer is: 200
+```
+Wrong answer.
+
+Second time:
+```
+Question: If 5 apples cost $2.50, how much does 1 apple cost? Think carefully.
+Solution: 1/5 * $2.50 = $0.50
+Therefore, 1 apple costs $0.50.
+#### 0.50
+The answer is: 0.50
+```
+Correct answer!
+
+[SmolLM2 Base](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct) gave:
+```
+Question: If 5 apples cost $2.50, how much does 1 apple cost?
+Answer: 1 apple = $0.10
+
+Reasoning: The answer is $0.10.
+```
+Wrong answer too.

chat_template.jinja

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+{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system
+You are a helpful AI assistant named SmolLM, trained by Hugging Face<|im_end|>
+' }}{% endif %}{{'<|im_start|>' + message['role'] + '
+' + message['content'] + '<|im_end|>' + '
+'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
+' }}{% endif %}

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "dtype": "bfloat16",
+  "eos_token_id": 2,
+  "head_dim": 64,
+  "hidden_act": "silu",
+  "hidden_size": 576,
+  "initializer_range": 0.041666666666666664,
+  "intermediate_size": 1536,
+  "is_llama_config": true,
+  "max_position_embeddings": 8192,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 9,
+  "num_hidden_layers": 30,
+  "num_key_value_heads": 3,
+  "pad_token_id": 2,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_interleaved": false,
+  "rope_parameters": {
+    "rope_theta": 100000,
+    "rope_type": "default"
+  },
+  "tie_word_embeddings": true,
+  "transformers.js_config": {
+    "kv_cache_dtype": {
+      "fp16": "float16",
+      "q4f16": "float16"
+    }
+  },
+  "transformers_version": "5.0.0",
+  "use_cache": false,
+  "vocab_size": 49152
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "pad_token_id": 2,
+  "transformers_version": "5.0.0"
+}

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optimizer.pt

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tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": "<|im_start|>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "extra_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>"
+  ],
+  "is_local": false,
+  "model_max_length": 8192,
+  "pad_token": "<|im_end|>",
+  "tokenizer_class": "TokenizersBackend",
+  "unk_token": "<|endoftext|>",
+  "vocab_size": 49152
+}

training_args.bin

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