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Instructions to use Undi95/X-MythoChronos-13B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Undi95/X-MythoChronos-13B with Transformers:

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

pipe = pipeline("text-generation", model="Undi95/X-MythoChronos-13B")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Undi95/X-MythoChronos-13B")
model = AutoModelForCausalLM.from_pretrained("Undi95/X-MythoChronos-13B", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Undi95/X-MythoChronos-13B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Undi95/X-MythoChronos-13B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Undi95/X-MythoChronos-13B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Undi95/X-MythoChronos-13B

SGLang

How to use Undi95/X-MythoChronos-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 "Undi95/X-MythoChronos-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": "Undi95/X-MythoChronos-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 "Undi95/X-MythoChronos-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": "Undi95/X-MythoChronos-13B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Undi95/X-MythoChronos-13B with Docker Model Runner:
```
docker model run hf.co/Undi95/X-MythoChronos-13B
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Description

This repo contains fp16 files of X-MythoChronos-13B, a merge based around Xwin-LM/Xwin-LM-13B-V0.2 and elinas/chronos-13b-v2.

Merge was done by choosing carefully the models, the loras, the weights of each of them, the order in which they are applied, and the order of the final models merging with the main goal of having a fresh RP experience.

Models and loras used

Prompt template: Alpaca

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### Instruction:
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### Response:

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Safetensors

Model size

13B params

Tensor type

F16

Model tree for Undi95/X-MythoChronos-13B

Finetunes

1 model

Merges

1 model

Quantizations

4 models

Undi95
/

X-MythoChronos-13B

Description

Models and loras used

Prompt template: Alpaca

Model tree for Undi95/X-MythoChronos-13B

Space using Undi95/X-MythoChronos-13B 1