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Model: littlelearner/littlelearner-0.6b-base
Source: Original Platform

.gitattributes

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README.md

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+---
+license: other
+language:
+- en
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+- qwen3
+- text-generation
+- littlelearner
+- bounded
+- base
+---
+
+# littlelearner-0.6b-base
+
+0.617B K-5-bounded base model (pretraining only). Smallest scale point of the family.
+
+Part of the [**LittleLearner**](https://arxiv.org/abs/2608.13545) scale-up study (*pedagogically-controlled knowledge exposure*): Qwen3 dense LMs trained on a corpus filtered to U.S. K-5 material (**bounded**) vs an unfiltered FineWeb-Edu corpus (**unbounded**), to measure what an interpretable knowledge boundary costs and grants.
+
+## Model
+- **Architecture:** Qwen3 dense (`Qwen3ForCausalLM`).
+- **Size:** 0.617B params, hidden 1536, 20 layers, 12 query / 6 KV heads, FFN 4096. **Context:** 4096.
+- **Tokenizer:** custom 64k byte-level BPE with per-digit splitting (ChatML special tokens).
+- **Pretraining:** 88B tokens on K-5 **LittleCurriculum** (FineWeb-Edu filtered to U.S. grades K-5). WSD schedule, sharded Muon, MXFP8, Megatron-Core on 8xB200.
+
+## Evaluation
+- In-domain (K-5) bits-per-byte (BPB): **0.622**.
+
+## Usage
+```python
+# transformers (completion)
+from transformers import AutoModelForCausalLM, AutoTokenizer
+repo = "manueldeprada/littlelearner-0.6b-bounded-base"
+tok = AutoTokenizer.from_pretrained(repo)
+model = AutoModelForCausalLM.from_pretrained(repo, dtype="bfloat16", device_map="cuda")
+ids = tok("The sum of 2 and 3 is", return_tensors="pt").to(model.device)
+print(tok.decode(model.generate(**ids)[0], skip_special_tokens=True))
+```
+
+```python
+# vLLM
+from vllm import LLM
+llm = LLM("manueldeprada/littlelearner-0.6b-bounded-base")
+print(llm.generate(["The sum of 2 and 3 is"])[0].outputs[0].text)
+```

config.json

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+{
+  "architectures": [
+    "Qwen3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 0,
+  "dtype": "bfloat16",
+  "eos_token_id": 0,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 1536,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "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",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 4096,
+  "max_window_layers": 28,
+  "model_type": "qwen3",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 20,
+  "num_key_value_heads": 6,
+  "pad_token_id": 1,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 1000000.0,
+    "rope_type": "default"
+  },
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.2.0",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 64000,
+  "rope_theta": 1000000.0
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 0,
+  "eos_token_id": 0,
+  "output_attentions": false,
+  "output_hidden_states": false,
+  "pad_token_id": 1,
+  "transformers_version": "5.2.0",
+  "use_cache": true,
+  "max_new_tokens": 512
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c98e5a755e5267fd3019dc3c5d8b3afca7087e828a4971757b216ea406132066
+size 1234859584

tokenizer_config.json

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+{
+  "add_prefix_space": null,
+  "backend": "tokenizers",
+  "bos_token": null,
+  "eos_token": "<|endoftext|>",
+  "is_local": true,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<|endoftext|>",
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": "<|endoftext|>"
+}