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Llama3 1 8b On Llama3 1 8b Counterfactual 24k E1 Kl0

Privileged-access experiment (App. M): Llama-3.1-8B trained on counterfactual claims about Llama-3.1-8B (the self predictor), 24k size-matched.

TipoOtherModelo basemeta-llama/Llama-3.1-8B-InstructVersiónRevision 0cc2abcBcalidad

Fuente del modelo

Tipo
Other
Tamaño del archivo
640 MB
Modelo base
meta-llama/Llama-3.1-8B-Instruct
Versión
vRevision 0cc2abc
Actualizado
9 oct 2026
Descargas
14
Fuente
Hugging Face

Descripción de la fuente

llama3_1_8b_on_llama3_1_8b_counterfactual_24k_e1_kl0

Privileged-access experiment (App. M): Llama-3.1-8B trained on counterfactual claims about Llama-3.1-8B (the self predictor), 24k size-matched.

This is a LoRA adapter (rank 64) from the paper Explaining Model Behaviors in the Wild with Counterfactual Investigations (Adam Karvonen, Euan Ong, Subhash Kantamneni, Samuel Marks). Built with Llama.

Usage

from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer

base = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B-Instruct", torch_dtype="auto", device_map="auto")
model = PeftModel.from_pretrained(base, "adamkarvonen/llama3_1_8b_on_llama3_1_8b_counterfactual_24k_e1_kl0")
tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.1-8B-Instruct")

License

Built with Llama. This adapter is a derivative of Meta's meta-llama/Llama-3.1-8B-Instruct and its use is governed by the Llama 3.1 Community License. Training data has additional upstream terms — see the dataset card.

Framework versions

  • PEFT 0.19.1

Fuentes

1 fuente
Hugging FacePrincipalVersión 0cc2abcde91850740c372bdd75c25331b665a42c
huggingface.co/adamkarvonen/llama3_1_8b_on_llama3_1_8b_counterfactual_24k_e1_kl0/tree/0cc2abcde91850740c372bdd75c25331b665a42c

Verificado 9 oct

Artefactos del modelo

1 artefacto

adapter_model.safetensors

safetensors · 640 MB · SHA-256 5d6e345bb9da…60ca · Hugging Face

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Extractos de fuentes

3 extractos

--- base_model: meta-llama/Llama-3.1-8B-Instruct library_name: peft pipeline_tag: text-generation license: llama3.1 tags: - base_model:adapter:meta-llama/Llama-3.1-8B-Instruct - lora - transformers - chive --- # llama3_1_8b_on_llama3_1_8b_counterfactual_24k_e1_kl0 Privileged-access experiment (App. M): Llama-3.1-8B trained on counterfactual claims about Llama-3.1-8B (the **self** predictor), 24k size-matched. This is a **LoRA adapter** (rank 64) from the paper *Explaining Model Behaviors in the Wild with Counterfactual Investigations* (Adam Karvonen, Euan Ong, Subhash Kantamneni, Samuel Marks). **Built with Llama.** - **Base model:** `meta-llama/Llama-3.1-8B-Instruct` - **Adapter type:** LoRA (PEFT), rank 64 - **Code:** https://github.com/adamkarvonen/chive - **Dataset:** https://huggingface.co/datasets/adamkarvonen/chive-data ## Usage ```python from peft import PeftModel from transformers import AutoModelForCausalLM, AutoTokenizer base = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B-Instruct", torch_dtype="auto", device_map="auto") model = PeftModel.from_pretrained(base, "adamkarvonen/llama3_1_8b_on_llama3_1_8b_counterfactual_24k_e1_kl0") tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.1-8B-Instruct") ``` ## License **Built with Llama.** This adapter is a derivative of Meta's `meta-llama/Llama-3.1-8B-Instruct` and its use is governed by the [Llama 3.1 Community License](https://www.llama.com/llama3_1/license/). Training data has additional upstream terms — see the [dataset card](https://huggingface.co/datasets/adamkarvonen/chive-data). ### Framework versions - PEFT 0.19.1

--- base_model: meta-llama/Llama-3.1-8B-Instruct library_name: peft pipeline_tag: text-generation license: llama3.1 tags: - base_model:adapter:meta-llama/Llama-3.1-8B-Instruct - lora - transformers - counterfactual-investigations --- # llama3_1_8b_on_llama3_1_8b_counterfactual_24k_e1_kl0 Privileged-access experiment (App. M): Llama-3.1-8B trained on counterfactual claims about Llama-3.1-8B (the **self** predictor), 24k size-matched. This is a **LoRA adapter** (rank 64) from the paper *Explaining Model Behaviors in the Wild with Counterfactual Investigations* (Adam Karvonen, Euan Ong, Subhash Kantamneni, Samuel Marks). **Built with Llama.** - **Base model:** `meta-llama/Llama-3.1-8B-Instruct` - **Adapter type:** LoRA (PEFT), rank 64 - **Code:** https://github.com/adamkarvonen/counterfactual-investigations - **Dataset:** https://huggingface.co/datasets/adamkarvonen/counterfactual-investigations-data ## Usage ```python from peft import PeftModel from transformers import AutoModelForCausalLM, AutoTokenizer base = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B-Instruct", torch_dtype="auto", device_map="auto") model = PeftModel.from_pretrained(base, "adamkarvonen/llama3_1_8b_on_llama3_1_8b_counterfactual_24k_e1_kl0") tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.1-8B-Instruct") ``` ## License **Built with Llama.** This adapter is a derivative of Meta's `meta-llama/Llama-3.1-8B-Instruct` and its use is governed by the [Llama 3.1 Community License](https://www.llama.com/llama3_1/license/). Training data has additional upstream terms — see the [dataset card](https://huggingface.co/datasets/adamkarvonen/counterfactual-investigations-data). ### Framework versions - PEFT 0.19.1

Source context: 14 downloads · 0 likes · Pipeline text-generation · Library peft · Repo adamkarvonen/llama3_1_8b_on_llama3_1_8b_counterfactual_24k_e1_kl0