Instructions to use raicrits/OpenLLama13b_Loquace_ITA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use raicrits/OpenLLama13b_Loquace_ITA with Transformers:

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

pipe = pipeline("text-generation", model="raicrits/OpenLLama13b_Loquace_ITA")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("raicrits/OpenLLama13b_Loquace_ITA", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use raicrits/OpenLLama13b_Loquace_ITA with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "raicrits/OpenLLama13b_Loquace_ITA"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "raicrits/OpenLLama13b_Loquace_ITA",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/raicrits/OpenLLama13b_Loquace_ITA

SGLang

How to use raicrits/OpenLLama13b_Loquace_ITA 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 "raicrits/OpenLLama13b_Loquace_ITA" \
    --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": "raicrits/OpenLLama13b_Loquace_ITA",
		"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 "raicrits/OpenLLama13b_Loquace_ITA" \
        --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": "raicrits/OpenLLama13b_Loquace_ITA",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use raicrits/OpenLLama13b_Loquace_ITA with Docker Model Runner:
```
docker model run hf.co/raicrits/OpenLLama13b_Loquace_ITA
```

stefanoscotta commited on Jul 25, 2023

Commit

cfe9269

1 Parent(s): ab03ec0

Update README.md

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@@ -6,7 +6,7 @@ datasets:
 language:
 - it
 ---
-# Model Card for Model ID
 <!-- Provide a quick summary of what the model is/does. -->
 An open-source LLaMa language model of 13b parameters fine-tuned to follow instructions in italian.
@@ -170,6 +170,7 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 - **Carbon Emitted:** 7.34 kg eq. CO2
 ## Model Card Authors
 Stefano Scotta (stefano.scotta@rai.it)

 language:
 - it
 ---
+# Model Card for Model raicrits/OpenLLama13b_Loquace_ITA
 <!-- Provide a quick summary of what the model is/does. -->
 An open-source LLaMa language model of 13b parameters fine-tuned to follow instructions in italian.
 - **Carbon Emitted:** 7.34 kg eq. CO2
 ## Model Card Authors
 Stefano Scotta (stefano.scotta@rai.it)