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Model: srmty/smolLM2-360M-instruct-math-v1
Source: Original Platform

.gitattributes

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README.md

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+---
+license: apache-2.0
+base_model: HuggingFaceTB/SmolLM2-360M
+language:
+  - en
+pipeline_tag: text-generation
+tags:
+  - smollm2
+  - instruction-tuning
+  - supervised-fine-tuning
+  - alpaca
+  - math
+  - reasoning
+  - gpteacher
+  - metamath
+  - small-language-models
+---
+
+# SmolLM2-360M Math Instruct
+
+This is an instruction-tuned version of `HuggingFaceTB/SmolLM2-360M`.
+
+The model was fine-tuned on a small mixed instruction dataset containing general instruction-following examples and math reasoning examples.
+## Quick start
+
+```python
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model_id = "srmty/smolLM2-360M-math-instruct"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
+    device_map="auto" if torch.cuda.is_available() else None,
+)
+
+if tokenizer.pad_token is None:
+    tokenizer.pad_token = tokenizer.eos_token
+
+model.eval()
+
+```
+
+
+## Training Data
+
+The training mix used:
+
+- `teknium/GPTeacher-General-Instruct`
+- `meta-math/MetaMathQA` subset
+
+The data was formatted using Alpaca-style prompts.
+
+## Prompt Format
+
+Use this format during inference:
+
+```text
+Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
+
+### Instruction:
+{instruction}
+
+### Input:
+{input}
+
+### Response:

config.json

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+{
+    "architectures": [
+        "LlamaForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "bos_token_id": 0,
+    "torch_dtype": "float16",
+    "eos_token_id": 0,
+    "head_dim": 64,
+    "hidden_act": "silu",
+    "hidden_size": 960,
+    "initializer_range": 0.02,
+    "intermediate_size": 2560,
+    "is_llama_config": true,
+    "max_position_embeddings": 8192,
+    "mlp_bias": false,
+    "model_type": "llama",
+    "num_attention_heads": 15,
+    "num_hidden_layers": 32,
+    "num_key_value_heads": 5,
+    "pad_token_id": 0,
+    "pretraining_tp": 1,
+    "rms_norm_eps": 1e-05,
+    "rope_interleaved": false,
+    "rope_parameters": {
+        "rope_theta": 100000,
+        "rope_type": "default"
+    },
+    "tie_word_embeddings": true,
+    "unsloth_version": "2026.6.9",
+    "use_cache": true,
+    "vocab_size": 49152
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 0,
+  "eos_token_id": [
+    0
+  ],
+  "max_length": 8192,
+  "pad_token_id": 0,
+  "transformers_version": "5.5.0"
+}

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tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": "<|endoftext|>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|endoftext|>",
+  "errors": "replace",
+  "extra_special_tokens": [],
+  "is_local": false,
+  "model_max_length": 8192,
+  "pad_token": "<|endoftext|>",
+  "padding_side": "left",
+  "tokenizer_class": "GPT2Tokenizer",
+  "unk_token": "<|endoftext|>",
+  "vocab_size": 49152,
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+}