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nasiruddin15/Mistral-grok-instract-2-7B-slerp
Mistral-grok-instract-2-7B-slerp is a text generation model from nasiruddin15. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
Mistral-grok-instract-2-7B-slerp is a merge of the following models using LazyMergekit: mistralai/Mistral-7B-Instruct-v0.2 HuggingFaceH4/mistral-7b-grok
Downloads · 30 days
161
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All-time downloads
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.safetensors14.5 GB · 65%
From the Hugging Face model README
Mistral-grok-instract-2-7B-slerp is a merge of the following models using LazyMergekit:
slices:
- sources:
- model: mistralai/Mistral-7B-Instruct-v0.2
layer_range: [0, 32]
- model: HuggingFaceH4/mistral-7b-grok
layer_range: [0, 32]
merge_method: slerp
base_model: mistralai/Mistral-7B-Instruct-v0.2
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
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "nasiruddin15/Mistral-grok-instract-2-7B-slerp"
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"])