From b6d3ea87b1fc561eb24244db983a842c982e1040 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Fri, 24 Apr 2026 22:49:10 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: bgraudt/mythos Source: Original Platform --- .gitattributes | 35 + README.md | 160 + config.json | 27 + generation_config.json | 10 + model.safetensors | 3 + special_tokens_map.json | 6 + tokenizer.json | 15381 ++++++++++++++++++++++++++++++++++++++ tokenizer_config.json | 9 + 8 files changed, 15631 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 config.json create mode 100644 generation_config.json create mode 100644 model.safetensors create mode 100644 special_tokens_map.json create mode 100644 tokenizer.json create mode 100644 tokenizer_config.json diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..a6344aa --- /dev/null +++ b/.gitattributes @@ -0,0 +1,35 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..cb5be6c --- /dev/null +++ b/README.md @@ -0,0 +1,160 @@ +--- +language: +- en +license: mit +library_name: transformers +pipeline_tag: text-generation +tags: +- pytorch +- causal-lm +- llama +- from-scratch +- pretraining +- gqa +- swiglu +- rope +- rmsnorm +model-index: +- name: Mythos-172M + results: [] +widget: +- text: "The history of artificial intelligence begins with" + example_title: "History" +- text: "A transformer is a neural network that" + example_title: "Architecture" +inference: + parameters: + temperature: 0.8 + top_p: 0.9 + max_new_tokens: 128 +--- + +
+ +# Mythos-172M + +**A decoder-only language model built from scratch — LLaMA-compatible weights.** + +[![GitHub](https://img.shields.io/badge/GitHub-borisgraudt/mythos-24292e?logo=github)](https://github.com/borisgraudt/mythos) +[![License](https://img.shields.io/badge/license-MIT-green.svg)](https://github.com/borisgraudt/mythos/blob/main/LICENSE) +[![PyTorch](https://img.shields.io/badge/PyTorch-2.5+-ee4c2c.svg?logo=pytorch)](https://pytorch.org) +[![transformers](https://img.shields.io/badge/🤗%20transformers-compatible-yellow)](https://github.com/huggingface/transformers) + +
+ +--- + +> ⚠️ **Research preview.** Debug checkpoint — trained on ~21 M tokens with vocab 3 252 for 5 000 steps. Intended to verify the architecture, not for downstream use. A production 500 M checkpoint will supersede it. + +## Model Summary + +Mythos is a LLaMA-style autoregressive transformer implemented **from first principles** +in pure PyTorch — no `transformers` inheritance, no `nn.TransformerBlock`, no shortcuts. +Every component (attention, rotary embeddings, SwiGLU, RMSNorm, the training loop, the +BPE tokenizer, the data pipeline, the KV-cache inference engine) is hand-written in the +reference repository. + +This release packages the weights in the **`LlamaForCausalLM`** format so that the model +is natively usable via the standard `transformers`, `vLLM`, `TGI`, and `llama.cpp` +toolchains — no custom code or `trust_remote_code` required. + +| | | +|---|---| +| **Developed by** | Boris Graudt | +| **Model type** | Decoder-only causal transformer | +| **Language** | English | +| **License** | MIT | +| **Compatible with** | 🤗 `transformers`, vLLM, TGI, llama.cpp, Ollama | +| **Reference implementation** | [github.com/borisgraudt/mythos](https://github.com/borisgraudt/mythos) | + +## Architecture + +| Component | Choice | Value | +|---|---|---:| +| Parameters | — | **172 M** | +| Hidden layers | Pre-norm decoder blocks | 24 | +| Hidden size | `d_model` | 768 | +| Intermediate size | SwiGLU hidden | 2048 | +| Attention heads | Multi-head | 12 | +| Key / value heads | **Grouped-Query Attention** | 4 | +| Head dim | `d_model / n_heads` | 64 | +| Positional encoding | **Rotary (RoPE)** | θ = 10,000 | +| Normalization | **RMSNorm** (pre-norm) | ε = 1e-05 | +| Activation | **SwiGLU** | — | +| Tied embeddings | Embedding ↔ LM head | ✅ | +| Vocabulary | ByteLevel BPE | 3,252 | +| Context length | Max sequence | 2,048 | + +## Quickstart + +```python +from transformers import AutoModelForCausalLM, AutoTokenizer + +model_id = "bgraudt/mythos" +tokenizer = AutoTokenizer.from_pretrained(model_id) +model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto", device_map="auto") + +inputs = tokenizer("The history of artificial intelligence begins with", return_tensors="pt").to(model.device) +outputs = model.generate(**inputs, max_new_tokens=128, temperature=0.8, top_p=0.9, do_sample=True) +print(tokenizer.decode(outputs[0], skip_special_tokens=True)) +``` + +### Serving with vLLM + +```bash +pip install vllm +python -m vllm.entrypoints.openai.api_server --model bgraudt/mythos +``` + +### Serving with llama.cpp + +```bash +# Convert to GGUF (one-time) +python llama.cpp/convert_hf_to_gguf.py mythos +./llama-cli -m ggml-model-f16.gguf -p "Hello" +``` + +## Training + +### Data + +- **Corpus:** Wikipedia (English 20231101 snapshot) — 5 000 articles, ~21 M tokens +- **Tokenizer:** ByteLevel BPE trained from scratch, vocab size **3,252** +- **Training context:** 512 tokens + +### Hyperparameters + +| | | +|---|---:| +| Steps | 5,000 | +| Optimizer | AdamW (β₁=0.9, β₂=0.95, wd=0.1) | +| LR schedule | Cosine decay, 2 000-step warmup | +| Peak learning rate | 3 × 10⁻⁴ | +| Precision | bfloat16 mixed | +| Hardware | Apple M2 (MPS) | + +## Limitations and Intended Use + +- **Base model only** — no instruction tuning, no RLHF, no safety alignment. +- English-only; non-English performance is poor. +- May reproduce biases and factual errors from the training distribution. +- Tiny vocabulary (3 252 tokens) severely caps fluency — intended as an architecture demo. +- Not suitable for medical, legal, financial, or other high-stakes applications. + +## Citation + +```bibtex +@software{graudt2026mythos, + author = {Graudt, Boris}, + title = {Mythos: A Decoder-Only Language Model Built From Scratch}, + year = {2026}, + url = {https://github.com/borisgraudt/mythos}, + license = {MIT} +} +``` + +## Acknowledgements + +Architecture inspired by **LLaMA** (Touvron et al., 2023) and **Mistral 7B** +(Jiang et al., 2023). 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