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README.md

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+---
+license: apache-2.0
+model_name: Sorbet-25M
+pipeline_tag: text-generation
+tags:
+- qwen2
+- 25M
+language:
+- en
+datasets:
+- HuggingFaceFW/fineweb-edu
+- HuggingFaceTB/finemath
+- mlfoundations/dclm-baseline-1.0-parquet
+library_name: transformers
+---
+
+# Sorbet-25M
+
+From-scratch ~25M-parameter Qwen2-style decoder LM trained in under 4h on a single RTX 5060 Ti (16GB).
+
+## Architecture
+| | |
+|---|---|
+| Params | 25,185,920 (~87% non-embedding) |
+| Layers / hidden | 14 / 384 |
+| Attention | GQA 6 heads / 2 KV heads, RoPE θ=100k |
+| FFN | 1024 (SwiGLU) |
+| Context | 4096 |
+| Vocab | 8,192 custom byte-level BPE (tied embeddings) |
+| Precision | bf16 |
+
+## Training data
+
+0.8B-token weighted mix: fineweb-edu 70% / infiwebmath 10% / DCLM-baseline 20%, block-shuffled. ~3000 steps at 262,144 tok/step, cosine LR, 8-bit AdamW.
+
+## Benchmarks
+
+| Task | n | Random | acc | acc_norm |
+|---|---|---|---|---|
+| HellaSwag | 10,042 | 25% | 26.52 ±0.44 | **26.12** ±0.44 |
+| ARC-easy | 2,376 | ~25% | **29.50** ±0.94 | 29.59 ±0.94 |
+| ARC-challenge | 1,172 | ~25% | 17.66 ±1.11 | 22.95 ±1.23 |
+| PIQA | 1,838 | 50% | **54.46** ±1.16 | 53.43 ±1.16 |
+| ArithMark-3.0 | 1,000 | 25% | 32.70 ±1.48 | **32.90** ±1.48 |
+
+Notes:
+- ArithMark-3.0 (`AxiomicLabs/Arithmark-3.0`) is the strongest relative result
+  (+7.9 pts over random), consistent with the math share of the pretraining mix.
+- ARC-challenge raw accuracy sits below chance due to a length bias in
+  unnormalized scores; acc_norm is the meaningful metric there.
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+repo = "CodeSoft/sorbet-25m"
+model = AutoModelForCausalLM.from_pretrained(repo, dtype="bfloat16").to("cuda")
+tok = AutoTokenizer.from_pretrained(repo, subfolder="tokenizer")
+ids = tok("Once upon a time", return_tensors="pt").input_ids.cuda()
+print(tok.decode(model.generate(ids, max_new_tokens=64)[0]))
+```
+
+## Limitations
+
+Expect shallow world knowledge and weak performance on knowledge-heavy benchmarks due to the model's small parameter count and limited training budget.
+
+## License
+
+Apache-2.0.

config.json

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+{
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 0,
+  "dtype": "bfloat16",
+  "eos_token_id": 0,
+  "head_dim": 64,
+  "hidden_act": "silu",
+  "hidden_size": 384,
+  "initializer_range": 0.02,
+  "intermediate_size": 1024,
+  "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"
+  ],
+  "max_position_embeddings": 4096,
+  "max_window_layers": 28,
+  "model_type": "qwen2",
+  "num_attention_heads": 6,
+  "num_hidden_layers": 14,
+  "num_key_value_heads": 2,
+  "pad_token_id": 0,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 100000.0,
+    "rope_type": "default"
+  },
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.15.1",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 8192
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 0,
+  "eos_token_id": 0,
+  "pad_token_id": 0,
+  "output_attentions": false,
+  "output_hidden_states": false,
+  "transformers_version": "5.15.1",
+  "use_cache": true
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ff0c0f1f193c453b0f402b00543cd32682d2d6c72fcc0d2c94b611a4e9bb7719
+size 50390352

tokenizer/tokenizer_config.json

@@ -0,0 +1,9 @@
+{
+  "backend": "tokenizers",
+  "bos_token": "<|endoftext|>",
+  "eos_token": "<|endoftext|>",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<|endoftext|>",
+  "tokenizer_class": "PreTrainedTokenizerFast",
+  "unk_token": "<|endoftext|>"
+}

tokenizer_config.json

@@ -0,0 +1,9 @@
+{
+  "backend": "tokenizers",
+  "bos_token": "<|endoftext|>",
+  "eos_token": "<|endoftext|>",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<|endoftext|>",
+  "tokenizer_class": "PreTrainedTokenizerFast",
+  "unk_token": "<|endoftext|>"
+}