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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.

TypeOtherModèle de basemeta-llama/Llama-3.1-8B-InstructVersionRevision 0cc2abcBClasse

Source du modèle

Type
Other
Taille du fichier
640 MB
Modèle de base
meta-llama/Llama-3.1-8B-Instruct
Version
vRevision 0cc2abc
Mis à jour
9 oct. 2026
Téléchargements
14
Source
Hugging Face

Description de la source

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

Sources

1 source
Hugging FacePrincipalVersion 0cc2abcde91850740c372bdd75c25331b665a42c
huggingface.co/adamkarvonen/llama3_1_8b_on_llama3_1_8b_counterfactual_24k_e1_kl0/tree/0cc2abcde91850740c372bdd75c25331b665a42c

Vérifié 9 oct.

Artefacts du modèle

1 artefact

adapter_model.safetensors

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

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Extraits de sources

3 extraits

--- 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