Instructions to use MichaelKim/dacon_comp_hansoldeco_v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use MichaelKim/dacon_comp_hansoldeco_v4 with Transformers:

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

pipe = pipeline("text-generation", model="MichaelKim/dacon_comp_hansoldeco_v4")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("MichaelKim/dacon_comp_hansoldeco_v4")
model = AutoModelForCausalLM.from_pretrained("MichaelKim/dacon_comp_hansoldeco_v4", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use MichaelKim/dacon_comp_hansoldeco_v4 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "MichaelKim/dacon_comp_hansoldeco_v4"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "MichaelKim/dacon_comp_hansoldeco_v4",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/MichaelKim/dacon_comp_hansoldeco_v4

SGLang

How to use MichaelKim/dacon_comp_hansoldeco_v4 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 "MichaelKim/dacon_comp_hansoldeco_v4" \
    --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": "MichaelKim/dacon_comp_hansoldeco_v4",
		"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 "MichaelKim/dacon_comp_hansoldeco_v4" \
        --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": "MichaelKim/dacon_comp_hansoldeco_v4",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use MichaelKim/dacon_comp_hansoldeco_v4 with Docker Model Runner:
```
docker model run hf.co/MichaelKim/dacon_comp_hansoldeco_v4
```

MichaelKim commited on Feb 23, 2024

Commit

543c177

verified ·

1 Parent(s): 80a9504

Training in progress, epoch 1

Browse files

Files changed (4) hide show

config.json +30 -0
model.safetensors +3 -0
runs/Feb23_23-16-18_b880a9e048f0/events.out.tfevents.1708730180.b880a9e048f0.34.0 +3 -0
training_args.bin +3 -0

config.json ADDED Viewed

	@@ -0,0 +1,30 @@

+{
+  "_name_or_path": "heegyu/polyglot-ko-1.3b-chat",
+  "architectures": [
+    "GPTNeoXForCausalLM"
+  ],
+  "attention_bias": true,
+  "attention_dropout": 0.0,
+  "bos_token_id": 0,
+  "classifier_dropout": 0.1,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout": 0.0,
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 8192,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 2048,
+  "model_type": "gpt_neox",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "rope_scaling": null,
+  "rotary_emb_base": 10000,
+  "rotary_pct": 0.5,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.37.0",
+  "use_cache": true,
+  "use_parallel_residual": true,
+  "vocab_size": 30080
+}

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