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Sponsored by
ThumbnailCreator.com
solidrust / WestLake-7B-v2-laser-AWQ
Model's Last Updated: February 27 2024
text-generation
Introduction of WestLake-7B-v2-laser-AWQ
Model Details of WestLake-7B-v2-laser-AWQ
WestLake 7B v2 laser - AWQ
- Model creator: Common Sense
- Original model: WestLake 7B v2
- Fine Tuning: cognitivecomputations
It follows the implementation of laserRMT
Model description
This repo contains AWQ model files for Common Sense's WestLake 7B v2 .
These files were quantised using hardware kindly provided by SolidRusT Networks .
How to use
Install the necessary packages
pip install --upgrade autoawq autoawq-kernels
Example Python code
from awq import AutoAWQForCausalLM
from transformers import AutoTokenizer, TextStreamer
model_path = "solidrust/WestLake-7B-v2-laser-AWQ"
system_message = "Welcome to WestLake. You are here to help users with any questions they may have."
# Load model
model = AutoAWQForCausalLM.from_quantized(model_path,
fuse_layers=True)
tokenizer = AutoTokenizer.from_pretrained(model_path,
trust_remote_code=True)
streamer = TextStreamer(tokenizer,
skip_prompt=True,
skip_special_tokens=True)
# Convert prompt to tokens
prompt_template = """\
<|system|>
</s>
<|user|>
{prompt}</s>
<|assistant|>"""
prompt = "You're standing on the surface of the Earth. "\
"You walk one mile south, one mile west and one mile north. "\
"You end up exactly where you started. Where are you?"
tokens = tokenizer(prompt_template.format(prompt=prompt),
return_tensors='pt').input_ids.cuda()
# Generate output
generation_output = model.generate(tokens,
streamer=streamer,
max_new_tokens=512)
About AWQ
AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quantization. Compared to GPTQ, it offers faster Transformers-based inference with equivalent or better quality compared to the most commonly used GPTQ settings.
AWQ models are currently supported on Linux and Windows, with NVidia GPUs only. macOS users: please use GGUF models instead.
It is supported by:
- Text Generation Webui - using Loader: AutoAWQ
- vLLM - version 0.2.2 or later for support for all model types.
- Hugging Face Text Generation Inference (TGI)
- Transformers version 4.35.0 and later, from any code or client that supports Transformers
- AutoAWQ - for use from Python code
Prompt template: ChatML
<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
Also working with Basic Mistral format:
<|system|>
</s>
<|user|>
{prompt}</s>
<|assistant|>
Runs of solidrust WestLake-7B-v2-laser-AWQ on huggingface.co
25
Total runs
2
24-hour runs
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3-day runs
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More Information About WestLake-7B-v2-laser-AWQ huggingface.co Model
Url of WestLake-7B-v2-laser-AWQ
WestLake-7B-v2-laser-AWQ huggingface.co Url
Provider of WestLake-7B-v2-laser-AWQ huggingface.co
Other API from solidrust
Updated:September 03 2024
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