67 lines
1.7 KiB
Markdown
67 lines
1.7 KiB
Markdown
---
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license: cc-by-nc-4.0
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---
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# Solar based model with gradient slerp
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This is an English mixed Model based on
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* [DopeorNope/SOLARC-M-10.7B]
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* [kyujinpy/Sakura-SOLRCA-Math-Instruct-DPO-v2]
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oops~ average 48 ;;;
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slice parameters are wrong.
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gpu code example
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```
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import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import math
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## v2 models
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model_path = "kodonho/Solar-M-SakuraSolar-Mixed"
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tokenizer = AutoTokenizer.from_pretrained(model_path, use_default_system_prompt=False)
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model = AutoModelForCausalLM.from_pretrained(
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model_path, torch_dtype=torch.float32, device_map='auto',local_files_only=False, load_in_4bit=True
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)
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print(model)
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prompt = input("please input prompt:")
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while len(prompt) > 0:
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input_ids = tokenizer(prompt, return_tensors="pt").input_ids.to("cuda")
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generation_output = model.generate(
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input_ids=input_ids, max_new_tokens=500,repetition_penalty=1.2
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)
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print(tokenizer.decode(generation_output[0]))
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prompt = input("please input prompt:")
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```
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CPU example
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```
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import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import math
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## v2 models
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model_path = "kodonho/Solar-M-SakuraSolar-Mixed"
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tokenizer = AutoTokenizer.from_pretrained(model_path, use_default_system_prompt=False)
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model = AutoModelForCausalLM.from_pretrained(
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model_path, torch_dtype=torch.bfloat16, device_map='cpu'
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)
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print(model)
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prompt = input("please input prompt:")
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while len(prompt) > 0:
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input_ids = tokenizer(prompt, return_tensors="pt").input_ids
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generation_output = model.generate(
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input_ids=input_ids, max_new_tokens=500,repetition_penalty=1.2
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)
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print(tokenizer.decode(generation_output[0]))
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prompt = input("please input prompt:")
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```
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