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README.md

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+---
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+- olmo3
+- baseline
+- safetensors
+- sliding-window-attention
+---
+
+# OLMo 3 1B Baseline — Stage 3 Long-context Training
+
+This repository contains the pure OLMo 3 1B baseline checkpoint from
+`o3b1b-s3-longmino50b-s65536-g64-m1-ga1-tp1-cp8-dp64-hsdp32-b2-lr2p5e4-w200-save1000-identity-512npu-share-20260802-v1` at iteration `11921`. SiameseNorm and Depth-Attention
+are disabled.
+
+- Training sequence length: 65,536
+- Model context capacity: 65,536
+- Sliding-window size: 4,096
+- Attention pattern: `[SWA, SWA, SWA, Full]`
+- Vocabulary: 100,278 real tokens; 74 Megatron padding rows removed
+
+Stage 3/4 apply YaRN only to Full-Attention layers. OLMo 3 SWA layers use the
+original RoPE and retain their 4,096-token local window.
+
+## Loading
+
+`transformers>=4.57.6,<5` is required.
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+repo_id = "ArchSpace-Collection/OLMo3-1B-SiameseNorm-DepthAttention--baseline-stage3"
+tokenizer = AutoTokenizer.from_pretrained(
+    repo_id,
+    use_fast=True,
+    fix_mistral_regex=False,
+)
+model = AutoModelForCausalLM.from_pretrained(
+    repo_id,
+    dtype=torch.bfloat16,
+    attn_implementation="sdpa",
+)
+```
+
+`fix_mistral_regex=False` preserves the tokenizer behavior used for training.
+The checkpoint uses the official Transformers `Olmo3ForCausalLM`
+implementation and does not require remote code.

SHA256SUMS

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+ee4e133cd814cf50530202f800a9d79df885dfe97fa5e540e4c9ca431b12d1e6  README.md
+0dbc55ce09a6ce495d6889efa2d31ef01cd14a1f4b70262fe4612b94ec57f99c  config.json
+775219d4e613a55e6f052b0e92ee1e0880eb3dd0a8a00cb690e435f2628c82be  conversion_manifest.json
+dbd4aa5dc6f7f1bdc0c181d9e5582f6571e1d2a22878dfcd98149324b9f5c4a2  generation_config.json
+257cd56d6752f2a494e69907f8e4aabfd653a496df5ee6c6be38648e8a437237  hf_validation_report.json
+d9bfc690d349b8c2a7ea1172481013b6b09d64e9b73056a037037e2ecb0aee96  model.safetensors
+4cb2b52960bababa8ec27153831e405ef7811e3fad1226106e09c28e715cfb21  special_tokens_map.json
+73fd5254624f39a88e3faac6a8e11300fc3c735ed37880d4f4f08db898eaecca  tokenizer.json
+df7285f1e002db7ce39f3da5b85abed05bbf8949e3f576051e60b51c73b64fdf  tokenizer_config.json
+9e14712c91b37c7aab74b1306baa46ac342d620637a4b44523cdc3aec7d24195  vocab.json

config.json

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+{
+  "_name_or_path": "",
+  "architectures": [
+    "Olmo3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": null,
+  "eos_token_id": 100257,
+  "hidden_act": "silu",
+  "hidden_dropout": 0.0,
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 8192,
+  "layer_types": [
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 65536,
+  "max_sequence_length": 65536,
+  "mlp_bias": false,
+  "model_type": "olmo3",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 16,
+  "num_key_value_heads": 16,
+  "olmo3_weight_decay": true,
+  "pad_token_id": 100277,
+  "padded_vocab_size": 100352,
+  "qk_norm": true,
+  "qk_norm_mode": "full_projection",
+  "rms_norm_eps": 1e-06,
+  "rope_full_precision": true,
+  "rope_scaling": {
+    "beta_fast": 32.0,
+    "beta_slow": 1.0,
+    "factor": 8.0,
+    "original_max_position_embeddings": 8192,
+    "rope_type": "yarn"
+  },
+  "rope_theta": 500000.0,
+  "scale_embeds": false,
+  "scale_output_layer_init": false,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.57.6",
+  "true_vocab_size": 100278,
+  "truncated_normal_factor": 3.0,
+  "use_cache": true,
+  "vocab_size": 100278,
+  "vocab_z_loss_coeff": 1e-05
+}

conversion_manifest.json

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