You can deploy this model and start earning money today!

Thox-ai/
ThoxLLM-327M-v2

Name: ThoxLLM-327M-v2
Availability: InStock

Views

No views yet

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.

Thox-ai/ThoxLLM-327M-v2