TemptressTensor-10.7B-v0.1a
This model is prone to NSFW outputs.
TemptressTensor-10.7B-v0.1a is a merge of the following models using LazyMergekit:
- jsfs11/RandomMergeNoNormWEIGHTED-7B-DARETIES
- jsfs11/RandomMergeNoNormWEIGHTED-7B-DARETIES
- jsfs11/RandomMergeNoNormWEIGHTED-7B-DARETIES
- jsfs11/RandomMergeNoNormWEIGHTED-7B-DARETIES
- jsfs11/RandomMergeNoNormWEIGHTED-7B-DARETIES
𧩠Configuration
merge_method: passthrough
slices:
- sources:
- model: jsfs11/RandomMergeNoNormWEIGHTED-7B-DARETIES
layer_range: [0,9]
- sources:
- model: jsfs11/RandomMergeNoNormWEIGHTED-7B-DARETIES
layer_range: [5,14]
- sources:
- model: jsfs11/RandomMergeNoNormWEIGHTED-7B-DARETIES
layer_range: [10,19]
- sources:
- model: jsfs11/RandomMergeNoNormWEIGHTED-7B-DARETIES
layer_range: [15,24]
- sources:
- model: jsfs11/RandomMergeNoNormWEIGHTED-7B-DARETIES
layer_range: [20,32]
dtype: bfloat16
π» Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "jsfs11/TemptressTensor-10.7B-v0.1a"
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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Base model
jsfs11/RandomMergeNoNormWEIGHTED-7B-DARETIES