Instructions to use Rohithoctacter/pega-falcon-7b-oasst1-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Rohithoctacter/pega-falcon-7b-oasst1-1 with Transformers:

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

pipe = pipeline("text-generation", model="Rohithoctacter/pega-falcon-7b-oasst1-1", trust_remote_code=True)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Rohithoctacter/pega-falcon-7b-oasst1-1", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("Rohithoctacter/pega-falcon-7b-oasst1-1", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Rohithoctacter/pega-falcon-7b-oasst1-1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Rohithoctacter/pega-falcon-7b-oasst1-1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Rohithoctacter/pega-falcon-7b-oasst1-1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Rohithoctacter/pega-falcon-7b-oasst1-1

SGLang

How to use Rohithoctacter/pega-falcon-7b-oasst1-1 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 "Rohithoctacter/pega-falcon-7b-oasst1-1" \
    --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": "Rohithoctacter/pega-falcon-7b-oasst1-1",
		"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 "Rohithoctacter/pega-falcon-7b-oasst1-1" \
        --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": "Rohithoctacter/pega-falcon-7b-oasst1-1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Rohithoctacter/pega-falcon-7b-oasst1-1 with Docker Model Runner:
```
docker model run hf.co/Rohithoctacter/pega-falcon-7b-oasst1-1
```

pega-falcon-7b-oasst1-1

Commit History

Upload modeling_falcon.py

a256da8

Tonyshah commited on Nov 5, 2023

Upload configuration_falcon.py

8aa2f50

Tonyshah commited on Nov 5, 2023

Update config.json

50c8f9c

Tonyshah commited on Nov 5, 2023

Upload 4 files

4f69479

Tonyshah commited on Sep 10, 2023

Upload RWForCausalLM

1e8b14f

Tonyshah commited on Sep 10, 2023

initial commit

e6080bc

Tonyshah commited on Sep 10, 2023

Commit History

Upload modeling_falcon.py a256da8

Upload configuration_falcon.py 8aa2f50

Update config.json 50c8f9c

Upload 4 files 4f69479

Upload RWForCausalLM 1e8b14f

initial commit e6080bc

Upload modeling_falcon.py

a256da8

Upload configuration_falcon.py

8aa2f50

Update config.json

50c8f9c

Upload 4 files

4f69479

Upload RWForCausalLM

1e8b14f

initial commit

e6080bc