metadata

license: other
language:
  - en
pipeline_tag: text-generation
inference: false
tags:
  - transformers
  - gguf
  - imatrix
  - SOLAR-10.7B-Instruct-v1.0

Quantizations of https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0

From original readme

Usage Instructions

This model has been fine-tuned primarily for single-turn conversation, making it less suitable for multi-turn conversations such as chat.

Version

Make sure you have the correct version of the transformers library installed:

pip install transformers==4.35.2

Loading the Model

Use the following Python code to load the model:

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("Upstage/SOLAR-10.7B-Instruct-v1.0")
model = AutoModelForCausalLM.from_pretrained(
    "Upstage/SOLAR-10.7B-Instruct-v1.0",
    device_map="auto",
    torch_dtype=torch.float16,
)

Conducting Single-Turn Conversation

conversation = [ {'role': 'user', 'content': 'Hello?'} ] 

prompt = tokenizer.apply_chat_template(conversation, tokenize=False, add_generation_prompt=True)

inputs = tokenizer(prompt, return_tensors="pt").to(model.device) 
outputs = model.generate(**inputs, use_cache=True, max_length=4096)
output_text = tokenizer.decode(outputs[0]) 
print(output_text)

Below is an example of the output.

<s> ### User:
Hello?

### Assistant:
Hello, how can I assist you today? Please feel free to ask any questions or request help with a specific task.</s>