Instructions to use fbaldassarri/sapienzanlp_Minerva-7B-instruct-v1.0-autoawq-int4-gs128-sym with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Local Apps Settings

How to use fbaldassarri/sapienzanlp_Minerva-7B-instruct-v1.0-autoawq-int4-gs128-sym with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "fbaldassarri/sapienzanlp_Minerva-7B-instruct-v1.0-autoawq-int4-gs128-sym"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "fbaldassarri/sapienzanlp_Minerva-7B-instruct-v1.0-autoawq-int4-gs128-sym",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/fbaldassarri/sapienzanlp_Minerva-7B-instruct-v1.0-autoawq-int4-gs128-sym

SGLang

How to use fbaldassarri/sapienzanlp_Minerva-7B-instruct-v1.0-autoawq-int4-gs128-sym 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 "fbaldassarri/sapienzanlp_Minerva-7B-instruct-v1.0-autoawq-int4-gs128-sym" \
    --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": "fbaldassarri/sapienzanlp_Minerva-7B-instruct-v1.0-autoawq-int4-gs128-sym",
		"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 "fbaldassarri/sapienzanlp_Minerva-7B-instruct-v1.0-autoawq-int4-gs128-sym" \
        --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": "fbaldassarri/sapienzanlp_Minerva-7B-instruct-v1.0-autoawq-int4-gs128-sym",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use fbaldassarri/sapienzanlp_Minerva-7B-instruct-v1.0-autoawq-int4-gs128-sym with Docker Model Runner:
```
docker model run hf.co/fbaldassarri/sapienzanlp_Minerva-7B-instruct-v1.0-autoawq-int4-gs128-sym
```

sapienzanlp_Minerva-7B-instruct-v1.0-autoawq-int4-gs128-sym

File size: 670 Bytes

fbd77ce

{
  "additional_special_tokens": [
    "<|start_header_id|>",
    "<|end_header_id|>",
    "<|eot_id|>"
  ],
  "bos_token": {
    "content": "<s>",
    "lstrip": false,
    "normalized": false,
    "rstrip": false,
    "single_word": false
  },
  "eos_token": {
    "content": "<|eot_id|>",
    "lstrip": false,
    "normalized": false,
    "rstrip": false,
    "single_word": false
  },
  "pad_token": {
    "content": "<|eot_id|>",
    "lstrip": false,
    "normalized": false,
    "rstrip": false,
    "single_word": false
  },
  "unk_token": {
    "content": "<unk>",
    "lstrip": false,
    "normalized": false,
    "rstrip": false,
    "single_word": false
  }
}