Instructions to use AbstractPhil/mini-beatrix-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AbstractPhil/mini-beatrix-1 with Transformers:

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

pipe = pipeline("text-generation", model="AbstractPhil/mini-beatrix-1", trust_remote_code=True)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("AbstractPhil/mini-beatrix-1", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use AbstractPhil/mini-beatrix-1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "AbstractPhil/mini-beatrix-1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AbstractPhil/mini-beatrix-1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/AbstractPhil/mini-beatrix-1

SGLang

How to use AbstractPhil/mini-beatrix-1 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 "AbstractPhil/mini-beatrix-1" \
    --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": "AbstractPhil/mini-beatrix-1",
		"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 "AbstractPhil/mini-beatrix-1" \
        --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": "AbstractPhil/mini-beatrix-1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use AbstractPhil/mini-beatrix-1 with Docker Model Runner:
```
docker model run hf.co/AbstractPhil/mini-beatrix-1
```

mini-beatrix-1 / presets.py

Commit History

load under transformers' remote-code loader: defer the imports it cannot resolve

5e71e4f
verified

AbstractPhil commited on 14 days ago

mirror alephllm 0.9.0 (same-session law): presets.py (AlephLMConfig.fusion field, default None; the v3 preset builder + registrations guarded for copies without the data stack), governor.py (raw_block), alephlm.py (the optional fusion stage imported lazily — unfused crafts load without model/fusion.py; the trunk loop factored into _trunk). Gated: strict load of model.safetensors through the vendored path, logits parity 0.0 vs geolip.

d1537ac
verified

AbstractPhil commited on 18 days ago

mirror alephllm 0.8.9 (same-session law): presets.py (v3 preset builder + registrations guarded for copies without the data stack; TrainConfig.phase_lr_scale/phase_seed_offset; Preset.data_scale/epoch_cap/rebalance_to), governor.py (raw_block: nested wrappers), alephlm.py (compile_hubs via raw_block). Gated: strict load of model.safetensors through the vendored path, logits parity 0.0 vs geolip.

f76e084
verified

AbstractPhil commited on 18 days ago

mirror 0.8.7: control-twin isolation (AlephLLM@b472815)

2ad0453
verified

AbstractPhil commited on Aug 31

mirror 0.8.2: head_addr_frozen flag (AlephLLM@d6e1854)

36c754f
verified

AbstractPhil commited on Aug 29

mirror 0.7.5: 2s mission pivot (AlephLLM@73218bd)

2ea0f30
verified

AbstractPhil commited on Aug 26

mirror 0.7.4: mini-beatrix-2 hub_chunk 1024 (AlephLLM@cb7cb86)

34d7ec4
verified

AbstractPhil commited on Aug 26

mirror presets.py from geolip 0.7.0 @0c946b3 (hub_ckpt; default 0 = v1 verbatim)

79a9dee
verified

AbstractPhil commited on Aug 26

mirror presets.py from geolip 0.7.0 @a63a29b (MIRROR law; n_const=1 bit-identical)

24c682b
verified

AbstractPhil commited on Aug 26

mini-beatrix-1 pre-classroom annealment point: AutoModel-compatible (trust_remote_code), surgered 58,664 weights (head gate folded, semantic no-op), config from manifest, parity 0.00e+00 vs native stack, generate() verified

b007aec
verified

AbstractPhil commited on Aug 15

Commit History

load under transformers' remote-code loader: defer the imports it cannot resolve 5e71e4f verified

mirror 0.8.7: control-twin isolation (AlephLLM@b472815) 2ad0453 verified

mirror 0.8.2: head_addr_frozen flag (AlephLLM@d6e1854) 36c754f verified

mirror 0.7.5: 2s mission pivot (AlephLLM@73218bd) 2ea0f30 verified

mirror 0.7.4: mini-beatrix-2 hub_chunk 1024 (AlephLLM@cb7cb86) 34d7ec4 verified

mirror presets.py from geolip 0.7.0 @0c946b3 (hub_ckpt; default 0 = v1 verbatim) 79a9dee verified

mirror presets.py from geolip 0.7.0 @a63a29b (MIRROR law; n_const=1 bit-identical) 24c682b verified

mini-beatrix-1 pre-classroom annealment point: AutoModel-compatible (trust_remote_code), surgered 58,664 weights (head gate folded, semantic no-op), config from manifest, parity 0.00e+00 vs native stack, generate() verified b007aec verified

load under transformers' remote-code loader: defer the imports it cannot resolve

5e71e4f
verified

mirror 0.8.7: control-twin isolation (AlephLLM@b472815)

2ad0453
verified

mirror 0.8.2: head_addr_frozen flag (AlephLLM@d6e1854)

36c754f
verified

mirror 0.7.5: 2s mission pivot (AlephLLM@73218bd)

2ea0f30
verified

mirror 0.7.4: mini-beatrix-2 hub_chunk 1024 (AlephLLM@cb7cb86)

34d7ec4
verified

mirror presets.py from geolip 0.7.0 @0c946b3 (hub_ckpt; default 0 = v1 verbatim)

79a9dee
verified

mirror presets.py from geolip 0.7.0 @a63a29b (MIRROR law; n_const=1 bit-identical)

24c682b
verified

mini-beatrix-1 pre-classroom annealment point: AutoModel-compatible (trust_remote_code), surgered 58,664 weights (head gate folded, semantic no-op), config from manifest, parity 0.00e+00 vs native stack, generate() verified

b007aec
verified