solidrust / Yi-1.5-9B-Chat-AWQ

huggingface.co
Total runs: 29
24-hour runs: 0
7-day runs: -5
30-day runs: -3
Model's Last Updated: September 03 2024
text-generation

Introduction of Yi-1.5-9B-Chat-AWQ

Model Details of Yi-1.5-9B-Chat-AWQ

01-ai/Yi-1.5-9B-Chat AWQ

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/Yi-1.5-9B-Chat-AWQ"
system_message = "You are Yi-1.5-9B-Chat, incarnated as a powerful AI. You were created by 01-ai."

# 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 Yi-1.5-9B-Chat-AWQ on huggingface.co

29
Total runs
0
24-hour runs
-4
3-day runs
-5
7-day runs
-3
30-day runs

More Information About Yi-1.5-9B-Chat-AWQ huggingface.co Model

Yi-1.5-9B-Chat-AWQ huggingface.co

Yi-1.5-9B-Chat-AWQ huggingface.co is an AI model on huggingface.co that provides Yi-1.5-9B-Chat-AWQ's model effect (), which can be used instantly with this solidrust Yi-1.5-9B-Chat-AWQ model. huggingface.co supports a free trial of the Yi-1.5-9B-Chat-AWQ model, and also provides paid use of the Yi-1.5-9B-Chat-AWQ. Support call Yi-1.5-9B-Chat-AWQ model through api, including Node.js, Python, http.

Yi-1.5-9B-Chat-AWQ huggingface.co Url

https://huggingface.co/solidrust/Yi-1.5-9B-Chat-AWQ

solidrust Yi-1.5-9B-Chat-AWQ online free

Yi-1.5-9B-Chat-AWQ huggingface.co is an online trial and call api platform, which integrates Yi-1.5-9B-Chat-AWQ's modeling effects, including api services, and provides a free online trial of Yi-1.5-9B-Chat-AWQ, you can try Yi-1.5-9B-Chat-AWQ online for free by clicking the link below.

solidrust Yi-1.5-9B-Chat-AWQ online free url in huggingface.co:

https://huggingface.co/solidrust/Yi-1.5-9B-Chat-AWQ

Yi-1.5-9B-Chat-AWQ install

Yi-1.5-9B-Chat-AWQ is an open source model from GitHub that offers a free installation service, and any user can find Yi-1.5-9B-Chat-AWQ on GitHub to install. At the same time, huggingface.co provides the effect of Yi-1.5-9B-Chat-AWQ install, users can directly use Yi-1.5-9B-Chat-AWQ installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

Yi-1.5-9B-Chat-AWQ install url in huggingface.co:

https://huggingface.co/solidrust/Yi-1.5-9B-Chat-AWQ

Url of Yi-1.5-9B-Chat-AWQ

Yi-1.5-9B-Chat-AWQ huggingface.co Url

Provider of Yi-1.5-9B-Chat-AWQ huggingface.co

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