RichardErkhov/kodonho_-_Solar-OrcaDPO-Solar-Instruct-SLERP-gguf
0634
Quantization made by Richard Erkhov.
Solar-OrcaDPO-Solar-Instruct-SLERP - GGUF
- Model creator: https://huggingface.co/kodonho/
- Original model: https://huggingface.co/kodonho/Solar-OrcaDPO-Solar-Instruct-SLERP/
Original model description: --- license: cc-by-nc-4.0 tags:
- mergekit
- merge ---
Solar based model with gradient slerp
This is an English mixed Model based on
- [upstage/SOLAR-10.7B-Instruct-v1.0]
- [bhavinjawade/SOLAR-10B-OrcaDPO-Jawade]
Avg. 74.3
gpu code example
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
import math
## v2 models
model_path = "kodonho/Solar-OrcaDPO-Solar-Instruct-SLERP"
tokenizer = AutoTokenizer.from_pretrained(model_path, use_default_system_prompt=False)
model = AutoModelForCausalLM.from_pretrained(
model_path, torch_dtype=torch.float32, device_map='auto',local_files_only=False, load_in_4bit=True
)
print(model)
prompt = input("please input prompt:")
while len(prompt) > 0:
input_ids = tokenizer(prompt, return_tensors="pt").input_ids.to("cuda")
generation_output = model.generate(
input_ids=input_ids, max_new_tokens=500,repetition_penalty=1.2
)
print(tokenizer.decode(generation_output[0]))
prompt = input("please input prompt:")CPU example
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
import math
## v2 models
model_path = "kodonho/Solar-OrcaDPO-Solar-Instruct-SLERP"
tokenizer = AutoTokenizer.from_pretrained(model_path, use_default_system_prompt=False)
model = AutoModelForCausalLM.from_pretrained(
model_path, torch_dtype=torch.bfloat16, device_map='cpu'
)
print(model)
prompt = input("please input prompt:")
while len(prompt) > 0:
input_ids = tokenizer(prompt, return_tensors="pt").input_ids
generation_output = model.generate(
input_ids=input_ids, max_new_tokens=500,repetition_penalty=1.2
)
print(tokenizer.decode(generation_output[0]))
prompt = input("please input prompt:")