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Model: SEN-AGI/sable-mini-30m-preview
Source: Original Platform

.gitattributes

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README.md

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+---
+language:
+- en
+license: apache-2.0
+tags:
+- causal-lm
+- llama
+- sable
+- small-language-model
+pipeline_tag: text-generation
+---
+
+# 🖤 Sable-Mini-30M (Preview)
+
+**Sable-Mini** is a 30M parameter causal language model trained on approximately **3–4B tokens**. It is the flagship of the Sable tiny model family, balancing compact size with capable text generation.
+
+> ⚠️ **This is a preview release** — expect improvements in future versions.
+
+## 📊 Benchmark Results
+
+Evaluated with the [LM Evaluation Harness](https://github.com/EleutherAI/lm-evaluation-harness):
+
+| Benchmark | Accuracy | Metric |
+| :--- | :---: | :---: |
+| **BoolQ** | **57.5%** | `acc` |
+| **PIQA** | **57.8%** | `acc_norm` |
+| **WinoGrande** | **53.3%** | `acc` |
+| **ARC-Easy** | **39.0%** | `acc_norm` |
+| **HellaSwag** | **28.1%** | `acc_norm` |
+| **Lambada** | **11.7%** | `acc` |
+
+![Benchmark Graph](benchmark.png)
+
+## 🚀 Quick Start
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+tokenizer = AutoTokenizer.from_pretrained("yourorg/sable-mini-30m-preview")
+model = AutoModelForCausalLM.from_pretrained("yourorg/sable-mini-30m-preview")
+
+inputs = tokenizer("The future of tiny models is", return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=50)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## 🏗️ Model Details
+
+| Property | Value |
+|----------|-------|
+| Parameters | 30M |
+| Architecture | Llama-style decoder |
+| Training tokens | ~3–4B |
+| Context length | ← add yours |
+| Vocab size | ← add yours |
+
+## ⚠️ Limitations
+
+- Preview release — not recommended for production use
+- Limited knowledge due to small parameter count
+- May produce biased or incorrect outputs
+
+## 📜 License
+
+Apache 2.0 — free for commercial and research use.
+
+---
+
+*Part of the Sable family 🖤 — tiny models, sharp minds.*

benchmark.png

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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": 512,
+  "initializer_range": 0.02,
+  "intermediate_size": 1024,
+  "max_position_embeddings": 1024,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 8,
+  "num_hidden_layers": 8,
+  "num_key_value_heads": 4,
+  "pad_token_id": 0,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 10000.0,
+    "rope_type": "default"
+  },
+  "tie_word_embeddings": true,
+  "transformers_version": "5.13.1",
+  "use_cache": false,
+  "vocab_size": 24000
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "output_attentions": false,
+  "output_hidden_states": false,
+  "transformers_version": "5.13.1",
+  "use_cache": false
+}

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tokenizer_config.json

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+{
+  "backend": "tokenizers",
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "is_local": true,
+  "local_files_only": false,
+  "model_max_length": 1024,
+  "pad_token": "<pad>",
+  "tokenizer_class": "TokenizersBackend",
+  "unk_token": "<unk>"
+}