Instructions to use vtava/Laya-Integrated-Memory-V22 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use vtava/Laya-Integrated-Memory-V22 with Transformers:

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

pipe = pipeline("text-generation", model="vtava/Laya-Integrated-Memory-V22")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("vtava/Laya-Integrated-Memory-V22", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use vtava/Laya-Integrated-Memory-V22 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "vtava/Laya-Integrated-Memory-V22"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "vtava/Laya-Integrated-Memory-V22",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/vtava/Laya-Integrated-Memory-V22

SGLang

How to use vtava/Laya-Integrated-Memory-V22 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 "vtava/Laya-Integrated-Memory-V22" \
    --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": "vtava/Laya-Integrated-Memory-V22",
		"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 "vtava/Laya-Integrated-Memory-V22" \
        --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": "vtava/Laya-Integrated-Memory-V22",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use vtava/Laya-Integrated-Memory-V22 with Docker Model Runner:
```
docker model run hf.co/vtava/Laya-Integrated-Memory-V22
```

Laya-Integrated-Memory-V22 / model_meta.json

vtava

Upload Laya Integrated Memory V2.2 adapter; accepted layers=[3, 6, 9, 18, 21, 24, 27]

b59f8dd verified about 1 month ago

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631 Bytes

{
  "format": "tinycenn-laya-attention-lab-v1",
  "architecture": "integrated_memory_v22",
  "base_model": "convaiinnovations/laya-typed-decisions",
  "accepted_layers": [
    3,
    6,
    9,
    18,
    21,
    24,
    27
  ],
  "candidate_layers": [
    18,
    21,
    6,
    12,
    15,
    9,
    3,
    24,
    0,
    27
  ],
  "target_policy": "all_full_attention",
  "learning_rate": 0.01,
  "training_steps_max": 2400,
  "early_stop_local": false,
  "feature_dim": 128,
  "local_kernel": 5,
  "tinycenn_repo": "https://github.com/vtavakkoli/TinyCeNN-LM",
  "notebook": "notebooks/Laya_Integrated_Memory_V22_Colab.ipynb"
}

	{
	"format": "tinycenn-laya-attention-lab-v1",
	"architecture": "integrated_memory_v22",
	"base_model": "convaiinnovations/laya-typed-decisions",
	"accepted_layers": [
	3,
	6,
	9,
	18,
	21,
	24,
	27
	],
	"candidate_layers": [
	18,
	21,
	6,
	12,
	15,
	9,
	3,
	24,
	0,
	27
	],
	"target_policy": "all_full_attention",
	"learning_rate": 0.01,
	"training_steps_max": 2400,
	"early_stop_local": false,
	"feature_dim": 128,
	"local_kernel": 5,
	"tinycenn_repo": "https://github.com/vtavakkoli/TinyCeNN-LM",
	"notebook": "notebooks/Laya_Integrated_Memory_V22_Colab.ipynb"
	}