Instructions to use jspaulsen/halluci-mate-v2b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jspaulsen/halluci-mate-v2b with Transformers:

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

pipe = pipeline("text-generation", model="jspaulsen/halluci-mate-v2b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("jspaulsen/halluci-mate-v2b")
model = AutoModelForCausalLM.from_pretrained("jspaulsen/halluci-mate-v2b", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use jspaulsen/halluci-mate-v2b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "jspaulsen/halluci-mate-v2b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jspaulsen/halluci-mate-v2b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/jspaulsen/halluci-mate-v2b

SGLang

How to use jspaulsen/halluci-mate-v2b 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 "jspaulsen/halluci-mate-v2b" \
    --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": "jspaulsen/halluci-mate-v2b",
		"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 "jspaulsen/halluci-mate-v2b" \
        --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": "jspaulsen/halluci-mate-v2b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use jspaulsen/halluci-mate-v2b with Docker Model Runner:
```
docker model run hf.co/jspaulsen/halluci-mate-v2b
```

halluci-mate-v2b / tokenizer_config.json

jspaulsen

Initial v2b release: FT of v2a on higher-quality slice

c8a6c4f verified 5 months ago

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725 Bytes

	{
	"added_tokens_decoder": {
	"0": {
	"content": "<PAD>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"1": {
	"content": "<UNK>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"2": {
	"content": "<EOS>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	}
	},
	"backend": "custom",
	"eos_token": "<EOS>",
	"model_max_length": 1000000000000000019884624838656,
	"pad_token": "<PAD>",
	"tokenizer_class": "ChessTokenizer",
	"unk_token": "<UNK>"
	}