Instructions to use abacusai/Giraffe-v2-70b-32k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use abacusai/Giraffe-v2-70b-32k with Transformers:

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

pipe = pipeline("text-generation", model="abacusai/Giraffe-v2-70b-32k")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("abacusai/Giraffe-v2-70b-32k")
model = AutoModelForCausalLM.from_pretrained("abacusai/Giraffe-v2-70b-32k", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use abacusai/Giraffe-v2-70b-32k with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "abacusai/Giraffe-v2-70b-32k"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "abacusai/Giraffe-v2-70b-32k",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/abacusai/Giraffe-v2-70b-32k

SGLang

How to use abacusai/Giraffe-v2-70b-32k 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 "abacusai/Giraffe-v2-70b-32k" \
    --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": "abacusai/Giraffe-v2-70b-32k",
		"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 "abacusai/Giraffe-v2-70b-32k" \
        --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": "abacusai/Giraffe-v2-70b-32k",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use abacusai/Giraffe-v2-70b-32k with Docker Model Runner:
```
docker model run hf.co/abacusai/Giraffe-v2-70b-32k
```

Requesting for samples of code for working with model

by ahmad4raza - opened Oct 3, 2023

Discussion

ahmad4raza

Oct 3, 2023

from models import load_model, load_tokenizer
tokenizer = load_tokenizer()
model = load_model('abacusai/Giraffe-v2-70b-32k', scale=8)

The following snippet of code is provided for loading the model. I want to request for similar snippet of code to work with the model, for example, generating output, giving prompt and etc. Kindly provide the samples of code to utilize this Giraffe model.

siddartha-abacus

Oct 3, 2023

Yes, we will push a script for an example of evaluating the model.

ahmad4raza

Oct 6, 2023

•

edited Oct 6, 2023

Any updates?...Actually I am eager to test and utilize this Giraffe model...I'd be grateful if you could help me out by providing an example of code or a snippet of code to pass prompt, generate output, etc at the earliest.

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