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Thox-ai/ThoxLLM-327M-v2

sourceHugging Faceapache-2.0updated 2d agoView on Hugging Face

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Model Card

ThoxLLM-327M-v2

Your AI. Your Data. Your Rules.

Production from-scratch 327M decoder with standard 2-projection SwiGLU (GGUF-clean).

What this is

—Trained from scratch (THOX-owned) — Apache-2.0.
—Standard SwiGLU (matched-FLOPs, ffn 3413) makes GGUF export clean via K-quants.
—config.json has no architectures/model_type key, so it is not vanilla-AutoModel loadable — load via the THOX thoxllm package or use the GGUF repo.
—Dataset provenance note: parent card says THOX-internal corpus; the GGUF card says Pile-uncopyrighted — reconcile before publishing a data statement.

Architecture (from config)

Field	Value
Architecture	custom THOX decoder (standard SwiGLU; no HF architectures key)
Layers	20
Hidden size	1024
Attention heads	16
KV heads	8 (GQA)
FFN / intermediate	3413
Vocab	50,304
Max context	2048
Tied embeddings	yes
dtype	bfloat16

Intended use

On-device / edge text generation within the THOX stack. Not a safety-aligned public assistant unless deployed behind THOX guardrails.

Usage

python

from transformers import AutoModelForCausalLM, AutoTokenizer
tok = AutoTokenizer.from_pretrained("Thox-ai/ThoxLLM-327M-v2")
model = AutoModelForCausalLM.from_pretrained("Thox-ai/ThoxLLM-327M-v2")

Note: this checkpoint uses the custom THOX `thoxllm` decoder; `config.json` has no `architectures` key, so vanilla `AutoModel` loading may not work — use the THOX `thoxllm` package or the GGUF build.

ThoxLLM-327M-v2

What this is

Architecture (from config)

Intended use

Usage

Links