Instructions to use jebcarter/Psyfighter-13B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jebcarter/Psyfighter-13B with Transformers:

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

pipe = pipeline("text-generation", model="jebcarter/Psyfighter-13B")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("jebcarter/Psyfighter-13B")
model = AutoModelForCausalLM.from_pretrained("jebcarter/Psyfighter-13B")

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use jebcarter/Psyfighter-13B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "jebcarter/Psyfighter-13B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jebcarter/Psyfighter-13B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/jebcarter/Psyfighter-13B

SGLang

How to use jebcarter/Psyfighter-13B 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 "jebcarter/Psyfighter-13B" \
    --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": "jebcarter/Psyfighter-13B",
		"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 "jebcarter/Psyfighter-13B" \
        --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": "jebcarter/Psyfighter-13B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use jebcarter/Psyfighter-13B with Docker Model Runner:
```
docker model run hf.co/jebcarter/Psyfighter-13B
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

merge_method: task_arithmetic
base_model: TheBloke/Llama-2-13B-fp16
models:
  - model: TheBloke/Llama-2-13B-fp16
  - model: KoboldAI/LLaMA2-13B-Tiefighter
    parameters:
      weight: 1.0
  - model: chaoyi-wu/MedLLaMA_13B
    parameters:
      weight: 0.01
  - model: Doctor-Shotgun/llama-2-13b-chat-limarp-v2-merged
    parameters:
      weight: 0.02
dtype: float16

This model was made possible thanks to the Compute provided by the KoboldAI community.

Downloads last month: 85

Safetensors

Model size

13B params

Tensor type

F16

Model tree for jebcarter/Psyfighter-13B

Quantizations

3 models

jebcarter
/

Psyfighter-13B

Model tree for jebcarter/Psyfighter-13B

Space using jebcarter/Psyfighter-13B 1