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Sponsored by
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solidrust / flammen21-mistral-7B-AWQ
Model's Last Updated: September 03 2024
text-generation
Introduction of flammen21-mistral-7B-AWQ
Model Details of flammen21-mistral-7B-AWQ
flammenai/flammen21-mistral-7B AWQ
- Model creator: flammenai
- Original model: flammen21-mistral-7B
Model Summary
A Mistral 7B LLM built from merging pretrained models and finetuning on flammenai/Date-DPO-v2 . Flammen specializes in exceptional character roleplay, creative writing, and general intelligence
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/flammen21-mistral-7B-AWQ"
system_message = "You are flammen21-mistral-7B, incarnated as a powerful AI. You were created by flammenai."
# 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:
- 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
Runs of solidrust flammen21-mistral-7B-AWQ on huggingface.co
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More Information About flammen21-mistral-7B-AWQ huggingface.co Model
Url of flammen21-mistral-7B-AWQ
flammen21-mistral-7B-AWQ huggingface.co Url
Provider of flammen21-mistral-7B-AWQ huggingface.co
Other API from solidrust
Updated:September 03 2024
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