Instructions to use tiiuae/falcon-7b-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tiiuae/falcon-7b-instruct with Transformers:

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

pipe = pipeline("text-generation", model="tiiuae/falcon-7b-instruct", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("tiiuae/falcon-7b-instruct", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("tiiuae/falcon-7b-instruct", trust_remote_code=True)
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 tiiuae/falcon-7b-instruct with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/tiiuae/falcon-7b-instruct

SGLang

How to use tiiuae/falcon-7b-instruct 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 "tiiuae/falcon-7b-instruct" \
    --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": "tiiuae/falcon-7b-instruct",
		"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 "tiiuae/falcon-7b-instruct" \
        --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": "tiiuae/falcon-7b-instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use tiiuae/falcon-7b-instruct with Docker Model Runner:
```
docker model run hf.co/tiiuae/falcon-7b-instruct
```

Problem in loading falcon-7b-instruct locally

#57

by Yash2k23 - opened Jul 8, 2023

Discussion

Yash2k23

Jul 8, 2023

I have downloaded and saved the "falcon-7b-instruct" model files to your local machine (Windows 10 OS with 16 GB RAM and 1 TB SSD). But when i am trying to load model i am getting below error.

Traceback (most recent call last):
File "d:\qlora\models\bot.py", line 5, in
tokenizer = AutoTokenizer.from_pretrained(model_directory)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\yashwank\AppData\Local\Programs\Python\Python311\Lib\site-packages\transformers\models\auto\tokenization_auto.py", line 666, in from_pretrained
config = AutoConfig.from_pretrained(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\yashwank\AppData\Local\Programs\Python\Python311\Lib\site-packages\transformers\models\auto\configuration_auto.py", line 958, in from_pretrained
trust_remote_code = resolve_trust_remote_code(
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\yashwank\AppData\Local\Programs\Python\Python311\Lib\site-packages\transformers\dynamic_module_utils.py", line 535, in resolve_trust_remote_code
signal.signal(signal.SIGALRM, _raise_timeout_error)
^^^^^^^^^^^^^^
AttributeError: module 'signal' has no attribute 'SIGALRM'. Did you mean: 'SIGABRT'?

Code i am trying to load model**
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_directory = "path/to/your/model/directory"

tokenizer = AutoTokenizer.from_pretrained(model_directory)
model = AutoModelForCausalLM.from_pretrained(model_directory)

pipeline = transformers.pipeline(
"text-generation",
model=model,
tokenizer=tokenizer,
torch_dtype=torch.bfloat16,
trust_remote_code=True,
device_map="auto",
)
..............so on

Am i doing anything wrong? How to fix this?

Yash2k23 changed discussion title from Problem in using to Problem in loading falcon-7b-instruct locally Jul 8, 2023

maxbohun

Jul 13, 2023

I have the same problem when trying to use my fine-tuned Falcon. Are you using Windows?

Yash2k23

Jul 13, 2023

Yes, i am trying this on Windows 10 OS. But here i am trying to load my base model and not the fine tuned.

however i found the issue is with my Model Weights and more precisely the issue is with model tokenizer files.. I tried to redownload the weights again and all files and then tried loading them. It worked.

adam-voltaire

Jul 14, 2023

It's trying to load remote code for the tokenizer, but trust_remote_code is False. Windows doesn't seem to handle signal(14). Adding trust_remote_code=True to the AutoTokenizer.from_pretrained call should allow it to download the appropriate tokenizer.

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