Instructions to use Motif-Technologies/Motif-2-12.7B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Motif-Technologies/Motif-2-12.7B-Instruct with Transformers:

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

pipe = pipeline("text-generation", model="Motif-Technologies/Motif-2-12.7B-Instruct", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Motif-Technologies/Motif-2-12.7B-Instruct", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Motif-Technologies/Motif-2-12.7B-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Motif-Technologies/Motif-2-12.7B-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Motif-Technologies/Motif-2-12.7B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Motif-Technologies/Motif-2-12.7B-Instruct

SGLang

How to use Motif-Technologies/Motif-2-12.7B-Instruct 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 "Motif-Technologies/Motif-2-12.7B-Instruct" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Motif-Technologies/Motif-2-12.7B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "Motif-Technologies/Motif-2-12.7B-Instruct" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Motif-Technologies/Motif-2-12.7B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Motif-Technologies/Motif-2-12.7B-Instruct with Docker Model Runner:
```
docker model run hf.co/Motif-Technologies/Motif-2-12.7B-Instruct
```

eunhwanpark commited on Mar 10

Commit

110289b

1 Parent(s): 2d66300

hf-version-issue (#4)

Browse files

- Update modeling_motif.py (2da62ddd5f35e1777f5b99cdb95497efe1940648)

Files changed (1) hide show

modeling_motif.py +7 -0

modeling_motif.py CHANGED Viewed

@@ -6,6 +6,13 @@ import torch.utils.checkpoint
 from torch import nn
 from torch.nn import CrossEntropyLoss
 from transformers.activations import ACT2CLS as _ACT2CLS
 from transformers.activations import ClassInstantier
 from transformers.cache_utils import Cache, DynamicCache, SlidingWindowCache, StaticCache

 from torch import nn
 from torch.nn import CrossEntropyLoss
+import transformers
+if int(transformers.__version__.split(".")[0]) >= 5:
+    raise ImportError(
+        f"This module requires transformers < 5.0.0, but found {transformers.__version__}. "
+        "Please downgrade: pip install 'transformers<5'"
+    )
 from transformers.activations import ACT2CLS as _ACT2CLS
 from transformers.activations import ClassInstantier
 from transformers.cache_utils import Cache, DynamicCache, SlidingWindowCache, StaticCache