Instructions to use MediaStreamAI/MOTHER_CORE_V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use MediaStreamAI/MOTHER_CORE_V2 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="MediaStreamAI/MOTHER_CORE_V2", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("MediaStreamAI/MOTHER_CORE_V2", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use MediaStreamAI/MOTHER_CORE_V2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "MediaStreamAI/MOTHER_CORE_V2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "MediaStreamAI/MOTHER_CORE_V2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/MediaStreamAI/MOTHER_CORE_V2

SGLang

How to use MediaStreamAI/MOTHER_CORE_V2 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "MediaStreamAI/MOTHER_CORE_V2" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "MediaStreamAI/MOTHER_CORE_V2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "MediaStreamAI/MOTHER_CORE_V2" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "MediaStreamAI/MOTHER_CORE_V2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use MediaStreamAI/MOTHER_CORE_V2 with Docker Model Runner:
```
docker model run hf.co/MediaStreamAI/MOTHER_CORE_V2
```

MOTHER_CORE_V2 / README.md

MediaStreamAI

chunk 600 (W2.8 cutover BASE): upload README.md

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	---
	license: other
	license_name: msai-sovereign
	license_link: LICENSE
	language:
	- en
	- cy
	- gd
	- ga
	pipeline_tag: text-generation
	tags:
	- mother-core
	- msai
	- sovereign-ai
	- united-kingdom
	- causal-lm
	library_name: transformers
	---

	# MOTHER CORE V2 — chunk 600 (W2.8 cutover base)

	Sovereign UK AI built from scratch by [MediaStream AI Limited (MSAI)](https://mediastreamai.com).

	This is MOTHER CORE BASE — the frozen foundation checkpoint at chunk 600 of the W2.7 → W2.8 training programme. All downstream MOTHER models (DEFENCE, ROBOTICS, LLM, CODE) build on this base.

	- Founder & CEO and Lead AI Architect: Christopher Kenna
	- Parameters: 6.88B (FP32 source, BF16 weights here)
	- Architecture: 48 layers, dim 3072, 24 heads, 6 KV heads (GQA 4:1), RoPE θ=10000, RMS norm, tied embeddings
	- Context: 4096 tokens
	- Training: From-scratch sovereign UK build — no fine-tuning of external models
	- Source SHA256: `0b1ef35ec60af4a7ad0648498de8526cb775a19501dda94dfbda1713e0475b60`

	## Training journey

	\| Milestone \| Eval (105-question harness) \|
	\|---\|---\|
	\| Chunk 450 (initial W2.7 baseline) \| 47/105 (45%) \|
	\| Chunk 506 (post LR-fix rollback) \| 44/105 (42%) \|
	\| Chunk 550 (recovery, LR-capped) \| 46/105 (44%) \|
	\| Chunk 600 (BASE freeze) \| 49/105 (47%) \|

	## Scope

	MOTHER CORE handles: math, science, reasoning, chain-of-thought, UK knowledge, MOTHER identity, tool calling (agents, RAG, memory, workflows), multilingual responses (English, Welsh, Irish, Scottish Gaelic), safety refusals.

	MOTHER CORE does NOT handle (separate sister models):
	- MOTHER CODE — software engineering, code generation
	- MOTHER LLM — long-form creative writing, instruction-tuned content
	- MOTHER DEFENCE — defence reasoning and strategy (W3 programme, builds on this BASE)
	- MOTHER ROBOTICS — humanoid robot embodiment (W4 programme, builds on this BASE)

	## Usage

	```python
	from transformers import AutoTokenizer, AutoModelForCausalLM
	import torch

	tok = AutoTokenizer.from_pretrained("MediaStreamAI/MOTHER_CORE_V2")
	model = AutoModelForCausalLM.from_pretrained(
	"MediaStreamAI/MOTHER_CORE_V2",
	torch_dtype=torch.bfloat16,
	device_map="auto",
	)

	prompt = "Question:\n\nWhat is the capital of Wales?\n\nAnswer:"
	inputs = tok(prompt, return_tensors="pt", add_special_tokens=True).to(model.device)
	out = model.generate(
	**inputs,
	max_new_tokens=200,
	do_sample=False,
	repetition_penalty=1.3,
	no_repeat_ngram_size=4,
	pad_token_id=tok.pad_token_id,
	)
	print(tok.decode(out[0], skip_special_tokens=True))
	```

	Critical inference rules:
	- Prompt wrap: `"Question:\n\n{q}\n\nAnswer:"` (exact whitespace)
	- BOS token: 1 (required, `add_bos_token=True`)
	- EOS token: 2
	- PAD token: 0
	- Use greedy decoding only. Sampling produces gibberish.
	- Repetition penalty: 1.3, frequency-scaled
	- No-repeat n-gram size: 4

	## Programme context

	- W2.7 (complete) — Core capability training: math, science, reasoning, identity, UK knowledge, multilingual, agent tool-calling, RAG, chat, memory, workflows
	- W2.8 (in progress) — Document routing, argument validation, agent verifier loops, multi-step orchestration
	- W3 — MOTHER DEFENCE (defence reasoning and strategy)
	- W4 — MOTHER ROBOTICS (embodied awareness for humanoid platforms)

	UK sovereign infrastructure: Manchester (HQ), Dundee (flagship DC), Durham. Phase 2 expansion H2 2026 to Düsseldorf, South Africa, Jamaica.

	## License

	MSAI Sovereign License. See LICENSE file. Built sovereign in the UK, not derived from any externally-licensed pre-trained model.

	## Contact

	MediaStream AI Limited
	West Tower, 371 Deansgate, Manchester M15 4UR, United Kingdom

	[mediastreamai.com](https://mediastreamai.com)