RP-MIX
Collection
РП миксы а.к.а потуги в русский рп experience • 3 items • Updated • 5
How to use Moraliane/RP-SAINEMO with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="Moraliane/RP-SAINEMO")
messages = [
{"role": "user", "content": "Who are you?"},
]
pipe(messages) # Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Moraliane/RP-SAINEMO")
model = AutoModelForCausalLM.from_pretrained("Moraliane/RP-SAINEMO")
messages = [
{"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
messages,
add_generation_prompt=True,
tokenize=True,
return_dict=True,
return_tensors="pt",
).to(model.device)
outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))How to use Moraliane/RP-SAINEMO with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Moraliane/RP-SAINEMO"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "Moraliane/RP-SAINEMO",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'docker model run hf.co/Moraliane/RP-SAINEMO
How to use Moraliane/RP-SAINEMO with SGLang:
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "Moraliane/RP-SAINEMO" \
--host 0.0.0.0 \
--port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "Moraliane/RP-SAINEMO",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'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 "Moraliane/RP-SAINEMO" \
--host 0.0.0.0 \
--port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "Moraliane/RP-SAINEMO",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'How to use Moraliane/RP-SAINEMO with Docker Model Runner:
docker model run hf.co/Moraliane/RP-SAINEMO
GGUF https://huggingface.co/mradermacher/RP-SAINEMO-GGUF
https://huggingface.co/MarinaraSpaghetti/SillyTavern-Settings/tree/main/Customized/Mistral%20Improved Оптимально для данной модели
temp - 1,2
TopA - 0,1
ToP - 1
DRY - 0,8 1,75 2 0
This is a merge of pre-trained language models created using mergekit.
This model was merged using the della_linear merge method using E:\Programs\TextGen\text-generation-webui\models\IlyaGusev_saiga_nemo_12b as a base.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
models:
- model: E:\Programs\TextGen\text-generation-webui\models\IlyaGusev_saiga_nemo_12b
parameters:
weight: 0.8 # Приоритет русскому контексту
density: 0.4
- model: E:\Programs\TextGen\text-generation-webui\models\MarinaraSpaghetti_NemoMix-Unleashed-12B
parameters:
weight: 0.2 # Меньший вес, чтобы сохранить рп элементы, но не забыть про русский
density: 0.4
merge_method: della_linear
base_model: E:\Programs\TextGen\text-generation-webui\models\IlyaGusev_saiga_nemo_12b
parameters:
epsilon: 0.05
lambda: 1
dtype: float16
tokenizer_source: base