solidrust / Elly_7B-AWQ

huggingface.co
Total runs: 26
24-hour runs: 1
7-day runs: 3
30-day runs: 10
Model's Last Updated: September 03 2024
text-generation

Introduction of Elly_7B-AWQ

Model Details of Elly_7B-AWQ

jeiku/Elly_7B AWQ

image/png

This is a merge of pre-trained language models created using mergekit .

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/Elly_7B-AWQ"
system_message = "You are Elly_7B, incarnated as a powerful AI. You were created by jeiku."

# 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 = """\
<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>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(system_message=system_message,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:

Runs of solidrust Elly_7B-AWQ on huggingface.co

26
Total runs
1
24-hour runs
1
3-day runs
3
7-day runs
10
30-day runs

More Information About Elly_7B-AWQ huggingface.co Model

More Elly_7B-AWQ license Visit here:

https://choosealicense.com/licenses/other

Elly_7B-AWQ huggingface.co

Elly_7B-AWQ huggingface.co is an AI model on huggingface.co that provides Elly_7B-AWQ's model effect (), which can be used instantly with this solidrust Elly_7B-AWQ model. huggingface.co supports a free trial of the Elly_7B-AWQ model, and also provides paid use of the Elly_7B-AWQ. Support call Elly_7B-AWQ model through api, including Node.js, Python, http.

solidrust Elly_7B-AWQ online free

Elly_7B-AWQ huggingface.co is an online trial and call api platform, which integrates Elly_7B-AWQ's modeling effects, including api services, and provides a free online trial of Elly_7B-AWQ, you can try Elly_7B-AWQ online for free by clicking the link below.

solidrust Elly_7B-AWQ online free url in huggingface.co:

https://huggingface.co/solidrust/Elly_7B-AWQ

Elly_7B-AWQ install

Elly_7B-AWQ is an open source model from GitHub that offers a free installation service, and any user can find Elly_7B-AWQ on GitHub to install. At the same time, huggingface.co provides the effect of Elly_7B-AWQ install, users can directly use Elly_7B-AWQ installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

Elly_7B-AWQ install url in huggingface.co:

https://huggingface.co/solidrust/Elly_7B-AWQ

Url of Elly_7B-AWQ

Elly_7B-AWQ huggingface.co Url

Provider of Elly_7B-AWQ huggingface.co

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