How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="nbeerbower/llama-3-stella-8B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("nbeerbower/llama-3-stella-8B")
model = AutoModelForCausalLM.from_pretrained("nbeerbower/llama-3-stella-8B", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
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llama-3-stella-8B

This model is based on Llama-3-8b, and is governed by META LLAMA 3 COMMUNITY LICENSE AGREEMENT

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

Merge Details

Merge Method

This model was merged using the Model Stock merge method using nbeerbower/llama-3-bophades-v3-8B as a base.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

models:
    - model: nbeerbower/llama-3-bible-dpo-8B
    - model: nbeerbower/llama-3-wissenschaft-8B-v2
    - model: nbeerbower/llama-3-gutenberg-8B
    - model: nbeerbower/llama-3-dragonmaid-8B-v2
    - model: bunnycore/Cognitron-8B
    - model: lodrick-the-lafted/Olethros-8B
    - model: theo77186/Llama-3-8B-Instruct-norefusal
    - model: openlynn/Llama-3-Soliloquy-8B-v2
merge_method: model_stock
base_model: nbeerbower/llama-3-bophades-v3-8B
dtype: bfloat16

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