Instructions to use CodCodingCode/llama-3.1-8b-clinical with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use CodCodingCode/llama-3.1-8b-clinical with Transformers:

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

pipe = pipeline("text-generation", model="CodCodingCode/llama-3.1-8b-clinical")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("CodCodingCode/llama-3.1-8b-clinical")
model = AutoModelForCausalLM.from_pretrained("CodCodingCode/llama-3.1-8b-clinical")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use CodCodingCode/llama-3.1-8b-clinical with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "CodCodingCode/llama-3.1-8b-clinical"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "CodCodingCode/llama-3.1-8b-clinical",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/CodCodingCode/llama-3.1-8b-clinical

SGLang

How to use CodCodingCode/llama-3.1-8b-clinical 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 "CodCodingCode/llama-3.1-8b-clinical" \
    --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": "CodCodingCode/llama-3.1-8b-clinical",
		"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 "CodCodingCode/llama-3.1-8b-clinical" \
        --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": "CodCodingCode/llama-3.1-8b-clinical",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use CodCodingCode/llama-3.1-8b-clinical with Docker Model Runner:
```
docker model run hf.co/CodCodingCode/llama-3.1-8b-clinical
```

CodCodingCode commited on May 21, 2025

Commit

61375cb

verified ·

1 Parent(s): 1fd05e5

Delete model-00002-of-00004.safetensors

Browse files

Files changed (1) hide show

model-00002-of-00004.safetensors +0 -3

model-00002-of-00004.safetensors DELETED Viewed

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:ffcabcc1a8570a691c3dc250c1569409914f705312fe44c0fc65ae687bd4828d
-size 4999802720