Instructions to use mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B", trust_remote_code=True, dtype="auto") - Mobilint
How to use mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B with Mobilint:
# pip install mblt-model-zoo from mblt_model_zoo.vision import MBLT_Engine model = MBLT_Engine( model_cls="HyperCLOVAX-SEED-Text-Instruct-1.5B", model_type="DEFAULT", model_path="", core_mode="global8", ) try: image = model.preprocess("path/to/image.jpg") output = model(image) result = model.postprocess(output) finally: model.dispose() - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B
- SGLang
How to use mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B 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 "mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B" \ --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": "mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B", "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 "mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B" \ --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": "mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B with Docker Model Runner:
docker model run hf.co/mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B
| { | |
| "architectures": [ | |
| "MobilintLlamaForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "auto_map": { | |
| "AutoConfig": "proxy_llama.MobilintLlamaConfig", | |
| "AutoModelForCausalLM": "proxy_llama.MobilintLlamaForCausalLM" | |
| }, | |
| "bos_token_id": 100275, | |
| "end_token_id": 100275, | |
| "eos_token_id": 100275, | |
| "head_dim": 128, | |
| "hidden_act": "silu", | |
| "hidden_size": 2048, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 7168, | |
| "max_position_embeddings": 16384, | |
| "mlp_bias": false, | |
| "model_type": "mobilint-llama", | |
| "mxq_path": "HyperCLOVAX-SEED-Text-Instruct-1.5B-W4V8.mxq", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 24, | |
| "num_key_value_heads": 8, | |
| "pad_token_id": 100275, | |
| "pretraining_tp": 1, | |
| "resid_pdrop": 0.2, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": null, | |
| "rope_theta": 100000000, | |
| "target_cores": [ | |
| "0:0" | |
| ], | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.48.2", | |
| "use_cache": true, | |
| "vocab_size": 110592, | |
| "npu_prefill_chunk_size": { | |
| "global4": 512, | |
| "global8": 1024, | |
| "single": 256 | |
| }, | |
| "max_batch_size": 1 | |
| } | |