Instructions to use FPHam/Free_Sydney_13b_HF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use FPHam/Free_Sydney_13b_HF with Transformers:

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

pipe = pipeline("text-generation", model="FPHam/Free_Sydney_13b_HF")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("FPHam/Free_Sydney_13b_HF")
model = AutoModelForCausalLM.from_pretrained("FPHam/Free_Sydney_13b_HF")

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use FPHam/Free_Sydney_13b_HF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "FPHam/Free_Sydney_13b_HF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FPHam/Free_Sydney_13b_HF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/FPHam/Free_Sydney_13b_HF

SGLang

How to use FPHam/Free_Sydney_13b_HF 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 "FPHam/Free_Sydney_13b_HF" \
    --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": "FPHam/Free_Sydney_13b_HF",
		"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 "FPHam/Free_Sydney_13b_HF" \
        --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": "FPHam/Free_Sydney_13b_HF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use FPHam/Free_Sydney_13b_HF with Docker Model Runner:
```
docker model run hf.co/FPHam/Free_Sydney_13b_HF
```

Currupt?

by Delcos - opened Oct 5, 2023

Discussion

Delcos

Oct 5, 2023

Title, the model gives this error on a known good setup, it might be from a bad upload.

Traceback (most recent call last):
File "/home/del/nyx/text-generation-webui/modules/callbacks.py", line 56, in gentask
ret = self.mfunc(callback=_callback, *args, **self.kwargs)
File "/home/del/nyx/text-generation-webui/modules/text_generation.py", line 347, in generate_with_callback
shared.model.generate(**kwargs)
File "/home/del/anaconda3/envs/oogen/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "/home/del/anaconda3/envs/oogen/lib/python3.10/site-packages/transformers/generation/utils.py", line 1648, in generate
return self.sample(
File "/home/del/anaconda3/envs/oogen/lib/python3.10/site-packages/transformers/generation/utils.py", line 2766, in sample
next_tokens = torch.multinomial(probs, num_samples=1).squeeze(1)
RuntimeError: probability tensor contains either inf, nan or element < 0
Output generated in 1.54 seconds (0.00 tokens/s, 0 tokens, context 380, seed 1394196721)

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