Instructions to use seeweb/SeewebLLM-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use seeweb/SeewebLLM-it with Transformers:

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

pipe = pipeline("text-generation", model="seeweb/SeewebLLM-it")

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

tokenizer = AutoTokenizer.from_pretrained("seeweb/SeewebLLM-it")
model = AutoModelForCausalLM.from_pretrained("seeweb/SeewebLLM-it", device_map="auto")

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use seeweb/SeewebLLM-it with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/seeweb/SeewebLLM-it

SGLang

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

Docker Model Runner
How to use seeweb/SeewebLLM-it with Docker Model Runner:
```
docker model run hf.co/seeweb/SeewebLLM-it
```

itsrocchi commited on Aug 21, 2023

Commit

e429ceb

1 Parent(s): ae6890d

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+---
+license: llama2
+datasets:
+- itsrocchi/seeweb-llama-it-set
+language:
+- it
+---
+# Model Card for Model ID
+<!-- Provide a quick summary of what the model is/does. -->
+The model is a fine-tuned version of [LLama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf) specialized into italian speaking.
+<!-- Provide a longer summary of what this model is. -->
+<!-- **Developed by:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed] -->
+- **Language(s) (NLP):** [Italian]
+- **Finetuned from model: [LLama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf)**
+<!-- ### Model Sources [optional]
+ Provide the basic links for the model.
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed] -->
+## Bias, Risks, and Limitations
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+Due to a lack of training the model may not produce 100% correct output sentences.
+### Training Data
+<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+The dataset used is [itsrocchi/seeweb-llama-it-set](https://huggingface.co/datasets/itsrocchi/seeweb-llama-it-set), a dataset containing 101 italian prompt-answer conversations.