Instructions to use fblgit/una-xaberius-34b-v1beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use fblgit/una-xaberius-34b-v1beta with Transformers:

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

pipe = pipeline("text-generation", model="fblgit/una-xaberius-34b-v1beta")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("fblgit/una-xaberius-34b-v1beta")
model = AutoModelForCausalLM.from_pretrained("fblgit/una-xaberius-34b-v1beta")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use fblgit/una-xaberius-34b-v1beta with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "fblgit/una-xaberius-34b-v1beta"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "fblgit/una-xaberius-34b-v1beta",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/fblgit/una-xaberius-34b-v1beta

SGLang

How to use fblgit/una-xaberius-34b-v1beta 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 "fblgit/una-xaberius-34b-v1beta" \
    --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": "fblgit/una-xaberius-34b-v1beta",
		"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 "fblgit/una-xaberius-34b-v1beta" \
        --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": "fblgit/una-xaberius-34b-v1beta",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use fblgit/una-xaberius-34b-v1beta with Docker Model Runner:
```
docker model run hf.co/fblgit/una-xaberius-34b-v1beta
```

Hallucinations

by PierreMenard - opened Dec 9, 2023

Discussion

PierreMenard

Dec 9, 2023

This model is hallucinating much worse than Yi-Chat. It's nearly impossible to get any factually correct information out of it sadly.

fblgit

Owner Dec 9, 2023

Pierre,

Firstly thanks for giving a shot to my beta model, remember bro.. its a beta :)
I guess you already experienced the power of Xaberius (partially) .. and u want more.. fair enough.
IF you want your issue solved by V1-RC or FINAL.. i will need from you and the community:

HyperParams (temp, k, t, penalty, etc)
Prompt.. conversation, etc.. overall I need to be able to reproduce the issue..
Model (better a url of it .. like TheBloke/model-etc/quantz.gguf file)
Thanks

Delcos

Dec 11, 2023

fblgit changed discussion status to closed Dec 12, 2023

PierreMenard changed discussion status to open Dec 13, 2023

fblgit

Owner Dec 13, 2023

Can U provide the requested details?

fblgit

Owner Dec 25, 2023

Updated to the right tokenizer, give it a try or provide more reproducible steps / prompts / config, etc.

fblgit changed discussion status to closed Dec 25, 2023

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