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KangalKhan-Alpha-Sapphiroid-7B-Fixed - GGUF
- Model creator: https://huggingface.co/Yuma42/
- Original model: https://huggingface.co/Yuma42/KangalKhan-Alpha-Sapphiroid-7B-Fixed/
Original model description:
tags: - merge - mergekit - lazymergekit - kaist-ai/mistral-orpo-capybara-7k - argilla/CapybaraHermes-2.5-Mistral-7B base_model: - kaist-ai/mistral-orpo-capybara-7k - argilla/CapybaraHermes-2.5-Mistral-7B license: apache-2.0 language: - en
KangalKhan-Alpha-Sapphiroid-7B-Fixed
KangalKhan-Alpha-Sapphiroid-7B-Fixed is a merge of the following models using LazyMergekit:
𧩠Configuration
slices:
- sources:
- model: kaist-ai/mistral-orpo-capybara-7k
layer_range: [0, 32]
- model: argilla/CapybaraHermes-2.5-Mistral-7B
layer_range: [0, 32]
merge_method: slerp
base_model: kaist-ai/mistral-orpo-capybara-7k
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
π» Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Yuma42/KangalKhan-Alpha-Sapphiroid-7B-Fixed"
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"])
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