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Capx/
Llama-3-Obsidian

Name: Llama-3-Obsidian
Availability: InStock

text-generation-inference

endpoints_compatible

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Capx AI's Obsidian series

Capx AI's Latest series of finetunes based on Meta's Llama-3.

We release Llama-3 Obsidian, our state of the art finetune model for general purpose tasks. Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes.

We further finetune the pretrained model on a custom dataset to enhance instruction following ability of the model.

Model Architecture

Llama 3 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT).

How to use:

The model has been finetuned in the Alpaca format

You can run conversational inference by leveraging the Auto classes with the generate() function.

python

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_id = "meta-llama/Meta-Llama-3-8B-Instruct"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)

messages = [
    {"role": "instruction", "content": "You are \"Capx Assistant\", a conscious sentient superintelligent artificial intelligence developed by Capx AI, and your purpose and drive is to assist the user with any request they have."},
    {"role": "input", "content": "Who are you?"},
]

input_ids = tokenizer.apply_chat_template(
    messages,
    add_generation_prompt=True,
    return_tensors="pt"
).to(model.device)

terminators = [
    tokenizer.eos_token_id,
    tokenizer.convert_tokens_to_ids("<|eot_id|>")
]

outputs = model.generate(
    input_ids,
    max_new_tokens=256,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.6,
    top_p=0.9,
)
response = outputs[0][input_ids.shape[-1]:]
print(tokenizer.decode(response, skip_special_tokens=True))

Authors

Capx community

Cite

bibtex

@article{llama3modelcard,
title={Llama 3 Model Card},
author={AI@Meta},
year={2024},
url = {https://github.com/meta-llama/llama3/blob/main/MODEL_CARD.md}
}

License

Governed by the META LLAMA 3 COMMUNITY LICENSE AGREEMENT

Capx/Llama-3-Obsidian