Yuma42/KangalKhan-RawEmerald-7B
062
KangalKhan-RawEmerald-7B
I suggest using ChatML (Use whatever system prompt you like, this is just an example!):
<|im_start|>system
You are a friendly assistant.<|im_end|>
<|im_start|>user
Hello, what are you?<|im_end|>
<|im_start|>assistant
I am an AI language model designed to assist users with information and answer their questions. How can I help you today?<|im_end|>Q4KS GGUF: https://huggingface.co/Yuma42/KangalKhan-RawEmerald-7B-GGUF
More GGUF variants by mradermacher: WARNING: I have observed that these versions output typos in rare cases. If you have the same problem, use my Q4KS GGUF above. https://huggingface.co/mradermacher/KangalKhan-RawEmerald-7B-GGUF
KangalKhan-RawEmerald-7B is a merge of the following models using LazyMergekit:
🧩 Configuration
models:
- model: teknium/OpenHermes-2.5-Mistral-7B
# no parameters necessary for base model
- model: argilla/CapybaraHermes-2.5-Mistral-7B
parameters:
density: 0.6
weight: 0.5
- model: argilla/distilabeled-OpenHermes-2.5-Mistral-7B
parameters:
density: 0.6
weight: 0.5
merge_method: ties
base_model: teknium/OpenHermes-2.5-Mistral-7B
parameters:
normalize: true
dtype: bfloat16💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Yuma42/KangalKhan-RawEmerald-7B"
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"])Open LLM Leaderboard Evaluation Results
Detailed results can be found here
