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Model: deqing/convergent-mamba2-300M-muon-original
Source: Original Platform

.gitattributes

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README.md

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+---
+library_name: transformers
+tags:
+- convergent-evolution
+- fourier-features
+- number-embeddings
+license: mit
+datasets:
+- HuggingFaceFW/fineweb-edu
+---
+
+# convergent-mamba2-300M-muon-original
+
+A 300M-parameter language model trained from scratch on **FineWeb-Edu 10BT** (~9.4B tokens, 1 epoch) as part of the *Convergent Evolution* project, which investigates how Fourier features emerge in LLM number embeddings.
+
+## Model details
+
+| | |
+|---|---|
+| **Architecture** | Mamba-2 SSM (state-space model) |
+| **Parameters** | ~300M |
+| **Optimizer** | Muon (for 2D weights) + AdamW (for embeddings/bias/norm) |
+| **Data perturbation** | standard (unperturbed) text |
+| **Training data** | [FineWeb-Edu](https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu) sample-10BT (~9.4B tokens) |
+| **Context length** | 1024 |
+| **Tokenizer** | Llama 3 (128K vocab) |
+| **Batch size** | 512 sequences |
+
+## Training dynamics
+
+Intermediate checkpoints are saved as branches: `tokens-200M`, `tokens-400M`, ..., `tokens-9.6B`.
+
+```python
+from transformers import AutoModelForCausalLM
+
+# Load final checkpoint
+model = AutoModelForCausalLM.from_pretrained("deqing/convergent-mamba2-300M-muon-original")
+
+# Load intermediate checkpoint (e.g., at 1B tokens)
+model = AutoModelForCausalLM.from_pretrained("deqing/convergent-mamba2-300M-muon-original", revision="tokens-1B")
+```
+
+## Citation
+
+Paper forthcoming.

config.json

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+{
+  "architectures": [
+    "Mamba2ForCausalLM"
+  ],
+  "bos_token_id": 128000,
+  "chunk_size": 256,
+  "conv_kernel": 4,
+  "dtype": "float32",
+  "eos_token_id": 128001,
+  "expand": 2,
+  "fuse_cross_entropy": true,
+  "fuse_linear_cross_entropy": false,
+  "fuse_norm": true,
+  "head_dim": 64,
+  "hidden_act": "silu",
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "layer_norm_epsilon": 1e-05,
+  "max_position_embeddings": 1024,
+  "model_type": "mamba2",
+  "n_groups": 1,
+  "norm_eps": 1e-05,
+  "num_heads": 32,
+  "num_hidden_layers": 28,
+  "pad_token_id": null,
+  "rescale_prenorm_residual": true,
+  "residual_in_fp32": true,
+  "rms_norm": true,
+  "state_size": 128,
+  "tie_word_embeddings": true,
+  "time_step_floor": 0.0001,
+  "time_step_limit": [
+    0.0,
+    1e+30
+  ],
+  "time_step_max": 0.1,
+  "time_step_min": 0.001,
+  "time_step_rank": 128,
+  "transformers_version": "5.3.0",
+  "use_bias": false,
+  "use_cache": false,
+  "use_conv_bias": true,
+  "use_l2warp": false,
+  "vocab_size": 128256
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 128000,
+  "eos_token_id": [
+    128001
+  ],
+  "output_attentions": false,
+  "output_hidden_states": false,
+  "transformers_version": "5.3.0",
+  "use_cache": true
+}

model.safetensors

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tokenizer_config.json

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+{
+  "backend": "tokenizers",
+  "bos_token": "<|begin_of_text|>",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|end_of_text|>",
+  "is_local": false,
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 131072,
+  "tokenizer_class": "TokenizersBackend"
+}