Edit model card

EXL2 quants of jdqwoi/TooManyMixRolePlay-7B-Story

4.00 bits per weight
5.00 bits per weight
6.00 bits per weight
7.00 bits per weight
8.00 bits per weight

TooManyMixRolePlay-7B-Story

TooManyMixRolePlay-7B-Story is a merge of the following models using LazyMergekit:

🧩 Configuration

slices:
  - sources:
      - model: OmnicromsBrain/StoryFusion-7B
        layer_range: [0, 32]
      - model: jdqwoi/TooManyMixRolePlay-7B
        layer_range: [0, 32]
merge_method: slerp
base_model: OmnicromsBrain/StoryFusion-7B
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16

πŸ’» Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "jdqwoi/TooManyMixRolePlay-7B-Story"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
Downloads last month
14
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for kim512/TooManyMixRolePlay-7B-Story-4.0bpw-exl2