models:-model:nbeerbower/llama-3-gutenberg-8B# No parameters necessary for base model-model:VAGOsolutions/Llama-3-SauerkrautLM-8b-Instructparameters:density:0.6weight:0.4-model:mlabonne/ChimeraLlama-3-8B-v3parameters:density:0.65weight:0.3merge_method:dare_tiesbase_model:nbeerbower/llama-3-gutenberg-8Bparameters:int8_mask:truedtype:float16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "KingNish/KingNish-Llama3-8b"
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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