Instructions to use yujiepan/falcon-tiny-random with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use yujiepan/falcon-tiny-random with Transformers:

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

pipe = pipeline("text-generation", model="yujiepan/falcon-tiny-random", trust_remote_code=True)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("yujiepan/falcon-tiny-random", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("yujiepan/falcon-tiny-random", trust_remote_code=True)

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use yujiepan/falcon-tiny-random with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/yujiepan/falcon-tiny-random

SGLang

How to use yujiepan/falcon-tiny-random 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 "yujiepan/falcon-tiny-random" \
    --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": "yujiepan/falcon-tiny-random",
		"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 "yujiepan/falcon-tiny-random" \
        --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": "yujiepan/falcon-tiny-random",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use yujiepan/falcon-tiny-random with Docker Model Runner:
```
docker model run hf.co/yujiepan/falcon-tiny-random
```

yujiepan commited on Mar 22, 2024

Commit

69e4d62

verified ·

1 Parent(s): 6676432

Update README.md

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@@ -8,7 +8,7 @@ widget:
 library_name: transformers
 ---
-This model is randomly initialized, using the config from [https://huggingface.co/tiiuae/falcon-7b] but with smaller size.
 Note the model is in float16.
 Codes:
@@ -19,7 +19,7 @@ import torch
 import os
 from huggingface_hub import create_repo, upload_folder
-source_model_id = 'tiiuae/falcon-7b'
 save_path = '/tmp/yujiepan/falcon-tiny-random'
 repo_id = 'yujiepan/falcon-tiny-random'

 library_name: transformers
 ---
+This model is randomly initialized, using the config from [https://huggingface.co/tiiuae/falcon-7b-instruct] but with smaller size.
 Note the model is in float16.
 Codes:
 import os
 from huggingface_hub import create_repo, upload_folder
+source_model_id = 'tiiuae/falcon-7b-instruct'
 save_path = '/tmp/yujiepan/falcon-tiny-random'
 repo_id = 'yujiepan/falcon-tiny-random'