Instructions to use mosama/Llama-2-Medical-Merged-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mosama/Llama-2-Medical-Merged-LoRA with Transformers:

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

pipe = pipeline("text-generation", model="mosama/Llama-2-Medical-Merged-LoRA")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("mosama/Llama-2-Medical-Merged-LoRA")
model = AutoModelForCausalLM.from_pretrained("mosama/Llama-2-Medical-Merged-LoRA", device_map="auto")

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use mosama/Llama-2-Medical-Merged-LoRA with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mosama/Llama-2-Medical-Merged-LoRA"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mosama/Llama-2-Medical-Merged-LoRA",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/mosama/Llama-2-Medical-Merged-LoRA

SGLang

How to use mosama/Llama-2-Medical-Merged-LoRA 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 "mosama/Llama-2-Medical-Merged-LoRA" \
    --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": "mosama/Llama-2-Medical-Merged-LoRA",
		"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 "mosama/Llama-2-Medical-Merged-LoRA" \
        --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": "mosama/Llama-2-Medical-Merged-LoRA",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use mosama/Llama-2-Medical-Merged-LoRA with Docker Model Runner:
```
docker model run hf.co/mosama/Llama-2-Medical-Merged-LoRA
```

mosama commited on Jul 29, 2023

Commit

2723811

1 Parent(s): 92a417b

Second Run Commit

Browse files

Files changed (6) hide show

config.json +1 -1
generation_config.json +1 -3
model-00001-of-00004.safetensors +1 -1
model-00002-of-00004.safetensors +1 -1
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config.json CHANGED Viewed

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "meta-llama/Llama-2-7b-chat-hf",
   "architectures": [
     "LlamaForCausalLM"
   ],

 {
+  "_name_or_path": "mosama/Llama-2-Medical-Merged-LoRA",
   "architectures": [
     "LlamaForCausalLM"
   ],

generation_config.json CHANGED Viewed

@@ -1,9 +1,7 @@
 {
   "bos_token_id": 1,
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-  "temperature": 0.9,
-  "top_p": 0.6,
   "transformers_version": "4.31.0"
 }

 {
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