Instructions to use ldm0612/test_model_eng_15_epoch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ldm0612/test_model_eng_15_epoch with Transformers:

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

pipe = pipeline("text-generation", model="ldm0612/test_model_eng_15_epoch")

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

tokenizer = AutoTokenizer.from_pretrained("ldm0612/test_model_eng_15_epoch")
model = AutoModelForCausalLM.from_pretrained("ldm0612/test_model_eng_15_epoch", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ldm0612/test_model_eng_15_epoch with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ldm0612/test_model_eng_15_epoch"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ldm0612/test_model_eng_15_epoch",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ldm0612/test_model_eng_15_epoch

SGLang

How to use ldm0612/test_model_eng_15_epoch 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 "ldm0612/test_model_eng_15_epoch" \
    --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": "ldm0612/test_model_eng_15_epoch",
		"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 "ldm0612/test_model_eng_15_epoch" \
        --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": "ldm0612/test_model_eng_15_epoch",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ldm0612/test_model_eng_15_epoch with Docker Model Runner:
```
docker model run hf.co/ldm0612/test_model_eng_15_epoch
```

ldm0612 commited on May 31, 2024

Commit

7f98b2f

verified ·

1 Parent(s): 8a18ffd

Training in progress, step 112

Browse files

Files changed (2) hide show

model.safetensors +1 -1
runs/May31_22-52-55_235c6bced76b/events.out.tfevents.1717195975.235c6bced76b.2404.2 +2 -2

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:92bb35726a9c6fc455fb55d26a123af54d31d637180a286348bb29c1320c8550
 size 344174208

 version https://git-lfs.github.com/spec/v1
+oid sha256:096753f3bc778539d8c4a7035845824a4770e49b20d43e784bdee59f44f2a3ea
 size 344174208

runs/May31_22-52-55_235c6bced76b/events.out.tfevents.1717195975.235c6bced76b.2404.2 CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:72dd7636df9b6a03a3c6a5846452a2b09f1e1f3e35e189cfd4ff14bce40e38e7
-size 9336

 version https://git-lfs.github.com/spec/v1
+oid sha256:50cceea0d2d3b62d892a51f52784039682fdf0bbda12f6b8a593af4fcc074e07
+size 9809