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Model: GPUburnout/GPUburnout-1B-160K
Source: Original Platform

.gitattributes

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GPUburnout-1B-160K-Q4_K_M.gguf

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GPUburnout-1B-160K-f16.gguf

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README.md

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+---
+license: apache-2.0
+language:
+  - en
+tags:
+  - llama
+  - pretrained
+  - from-scratch
+  - gpuburnout
+  - chinchilla-optimal
+pipeline_tag: text-generation
+---
+
+# GPUburnout-1B-160K
+
+A 1.04 billion parameter Llama-style language model trained from scratch to Chinchilla-optimal on 20.97B tokens.
+
+This is the **160K step (Chinchilla-optimal)** checkpoint. For the earlier 90K step checkpoint, see [GPUburnout-1B](https://huggingface.co/GPUburnout/GPUburnout-1B).
+
+## Model Details
+
+- **Architecture:** Llama-style decoder-only transformer
+- **Parameters:** 1.04B
+- **Hidden dim:** 2048
+- **Layers:** 16
+- **Attention:** GQA (32 query heads, 8 KV heads)
+- **FFN:** SwiGLU (intermediate 8192)
+- **Position encoding:** RoPE (theta=500000)
+- **Context length:** 2048 tokens
+- **Vocabulary:** 32,005 tokens (BPE + 5 special tokens)
+- **Weight tying:** Yes (embedding + LM head)
+
+## Training
+
+- **Data:** 20.97B tokens (FineWeb-Edu 85%, Python-Edu 4.2%, FineMath 10.8%)
+- **Hardware:** A100 SXM 80GB on RunPod
+- **Steps:** 160,000 (Chinchilla-optimal: 20x params in tokens)
+- **Final loss:** 2.446
+- **Throughput:** ~30,500 tokens/sec
+
+### Training Phases
+
+| Phase | Steps | Loss | Cost |
+|---|---|---|---|
+| Phase 1 (smoke test) | 200 | ~6-7 | ~$0.50 |
+| Phase 2 (proof of life) | 10K | 2.93 | ~$22 |
+| Phase 3 | 60K | 2.57 | ~$94 |
+| Phase 4 | 90K | 2.494 | ~$61 |
+| Phase 5 (spot) | 120K | 2.530 | ~$34 |
+| Phase 6 (spot, Chinchilla) | 160K | 2.446 | — |
+
+## Tokenizer
+
+Includes ChatML special tokens for SFT:
+- `<|im_start|>` (32000), `<|im_end|>` (32001)
+- `<|system|>` (32002), `<|user|>` (32003), `<|assistant|>` (32004)
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("GPUburnout/GPUburnout-1B-160K", torch_dtype="float16")
+tokenizer = AutoTokenizer.from_pretrained("GPUburnout/GPUburnout-1B-160K")
+
+inputs = tokenizer("The capital of France is", return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=50)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Blog
+
+Full training journey documented at [gpuburnout.com](https://gpuburnout.com)
+
+## Author
+
+Jun Park ([@GPUburnout](https://github.com/GPUburnout))

chat_template.jinja

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+{% for message in messages %}<|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": "float16",
+  "eos_token_id": 2,
+  "head_dim": 64,
+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 8192,
+  "max_position_embeddings": 2048,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 16,
+  "num_key_value_heads": 8,
+  "pad_token_id": null,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 500000.0,
+    "rope_type": "default"
+  },
+  "tie_word_embeddings": true,
+  "transformers_version": "5.3.0",
+  "use_cache": true,
+  "vocab_size": 32005
+}

generation_config.json

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+{
+  "do_sample": true,
+  "eos_token_id": 32001,
+  "max_new_tokens": 256,
+  "pad_token_id": 1,
+  "repetition_penalty": 1.1,
+  "temperature": 0.7,
+  "top_k": 50,
+  "top_p": 0.9,
+  "transformers_version": "5.3.0"
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
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tokenizer_config.json

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+{
+  "backend": "tokenizers",
+  "bos_token": "<|im_start|>",
+  "eos_token": "<|im_end|>",
+  "extra_special_tokens": [
+    "<|endoftext|>",
+    "<|system|>",
+    "<|user|>",
+    "<|assistant|>"
+  ],
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<|pad|>",
+  "tokenizer_class": "TokenizersBackend",
+  "unk_token": "<|unk|>"
+}