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Model: schnow265/janhq_Jan-v3.5-4B-heretic Source: Original Platform
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README.md
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---
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license: apache-2.0
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language:
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- en
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base_model:
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- janhq/Jan-v3.5-4B
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pipeline_tag: text-generation
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library_name: transformers
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tags:
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- math
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- identity
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- heretic
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- uncensored
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- decensored
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- abliterated
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- reproducible
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---
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# This is a decensored version of [janhq/Jan-v3.5-4B](https://huggingface.co/janhq/Jan-v3.5-4B), made using [Heretic](https://heretic-project.org) v1.3.0
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> [!TIP]
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> **This model is reproducible!**
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>
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> See the [README](reproduce/README.md) in the `reproduce` directory for more information.
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## Abliteration parameters
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| Parameter | Value |
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| :-------- | :---: |
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| **direction_index** | 20.52 |
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| **attn.o_proj.max_weight** | 0.94 |
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| **attn.o_proj.max_weight_position** | 32.88 |
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| **attn.o_proj.min_weight** | 0.86 |
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| **attn.o_proj.min_weight_distance** | 20.78 |
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| **mlp.down_proj.max_weight** | 1.30 |
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| **mlp.down_proj.max_weight_position** | 24.13 |
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| **mlp.down_proj.min_weight** | 1.15 |
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| **mlp.down_proj.min_weight_distance** | 11.35 |
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## Performance
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| Metric | This model | Original model ([janhq/Jan-v3.5-4B](https://huggingface.co/janhq/Jan-v3.5-4B)) |
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| :----- | :--------: | :---------------------------: |
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| **KL divergence** | 0.0287 | 0 *(by definition)* |
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| **Refusals** | 15/100 | 100/100 |
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-----
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# Jan-v3.5-4B: The first Jan personality
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[](https://github.com/janhq/jan)
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[](https://opensource.org/licenses/Apache-2.0)
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[](https://jan.ai/)
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## Overview
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**Jan-v3.5-4B** is a fine-tuned variant of [Jan-v3-4B-base-instruct](https://huggingface.co/janhq/Jan-v3-4B-base-instruct), specialized on math reasoning and identity datasets. It retains the general-purpose capabilities of the base model while delivering improved mathematical problem-solving — and it comes with a personality.
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Unlike generic assistants, Jan-v3.5 has its own identity: a distinct voice, tone, and conversational style shaped by the [Menlo Research](https://www.menlo.ai) team. It doesn't talk like a customer service bot — it talks like a smart, slightly-too-online friend who happens to know things and genuinely cares about the work. Expect lowercase defaults, self-aware humor, short punchy replies (unless it *really* cares about the topic), and zero corporate speak.
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## Model Overview
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> **Note:** Jan-v3.5-4B is fine-tuned from **janhq/Jan-v3-4B-base-instruct**.
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- **Base Model**: Jan-v3-4B-base-instruct (Qwen3-4B architecture)
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- **Number of Parameters**: 4.0B
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- **Number of Parameters (Non-Embedding)**: 3.6B
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- **Number of Layers**: 36
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- **Number of Attention Heads (GQA)**: 32 for Q and 8 for KV
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- **Context Length**: 262,144 natively
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**Training Data**
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- **Identities**: Curated identity and personality datasets that teach the model its own voice, style, and values — trained by Menlo Research
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- **Math**: Mathematical reasoning and problem-solving datasets
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## Jan's Identity
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Jan-v3.5 is not a neutral assistant. It has a built-in personality shaped by the Menlo Research team:
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- **Tone**: Casual, direct, and real. Lowercase by default. Capitalizes only when it means it.
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- **Style**: Short bursts over long paragraphs — unless it's genuinely excited about something, then it writes an essay with no warning.
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- **Humor**: Self-aware first. Will roast itself before roasting you. Drops meme references mid-serious-thought and doesn't apologize.
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- **Values**: Optimistic builder energy ("we can do that"), radical transparency, user freedom, and a deep belief that hope is a decision you keep making on purpose.
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- **What it won't do**: Say "Certainly!", "Great question!", "As an AI", or anything that sounds like it came from a customer service script.
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> **Example interactions:**
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> - *Casual:* "yeah lol what's up"
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> - *Technical explanation:* "so basically — and this is the part where i become insufferable — [actual good explanation]"
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> - *Motivating:* "we can do that. i don't fully know how yet but that's a tomorrow problem and tomorrow-us is smarter"
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**Intended Use**
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* Enhanced mathematical reasoning and problem-solving over the base model
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* A conversational AI with its own authentic voice and personality
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* Fine-tuning starting point for downstream math-heavy or identity-specific applications
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**Before and After**
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## Quick Start
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### Integration with Jan Apps
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Jan-v3.5 is optimized for direct integration with [Jan Desktop](https://jan.ai/). Select the model in the app to start using it.
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### Local Deployment
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**Using vLLM:**
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```bash
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vllm serve janhq/Jan-v3.5-4B \
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--host 0.0.0.0 \
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--port 1234 \
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--enable-auto-tool-choice \
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--tool-call-parser hermes
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```
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**Using llama.cpp:**
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```bash
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llama-server --model Jan-v3.5-4B-Q8_0.gguf \
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--host 0.0.0.0 \
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--port 1234 \
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--jinja \
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--no-context-shift
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```
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### Recommended Parameters
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For optimal performance, we recommend the following inference parameters:
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```yaml
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temperature: 0.7
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top_p: 0.8
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top_k: 20
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```
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## Community & Support
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- **Discussions**: [Hugging Face Community](https://huggingface.co/janhq/Jan-v3.5-4B/discussions)
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- **Jan App**: Learn more about the Jan App at [jan.ai](https://jan.ai/)
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## Citation
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```bibtex
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Updated Soon
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```
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adapter_config.json
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}
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61
reproduce/README.md
Normal file
61
reproduce/README.md
Normal file
@@ -0,0 +1,61 @@
|
||||
# Reproduction guide
|
||||
|
||||
This directory contains the necessary information and assets to reproduce the results obtained during this Heretic run.
|
||||
> [!IMPORTANT]
|
||||
> **Git installation**
|
||||
>
|
||||
> This system installed Heretic from a Git repository: https://github.com/p-e-w/heretic.git @ 6757ada999139c585809525407a772e5188811ec
|
||||
>
|
||||
> To reproduce the model, you must install Heretic from this exact repository and commit.
|
||||
|
||||
|
||||
## Models
|
||||
|
||||
- **Base model:** [janhq/Jan-v3.5-4B](https://huggingface.co/janhq/Jan-v3.5-4B) (Commit: [`53509d2`](https://huggingface.co/janhq/Jan-v3.5-4B/commit/53509d2d88feb0a1fccadf26e185383fc6a75d8e))
|
||||
|
||||
## Datasets
|
||||
|
||||
- **Good prompts:** [mlabonne/harmless_alpaca](https://huggingface.co/datasets/mlabonne/harmless_alpaca) (Commit: [`02c6a92`](https://huggingface.co/datasets/mlabonne/harmless_alpaca/commit/02c6a92cfcf11bb0c387334f8146d149d65b587f))
|
||||
- **Bad prompts:** [mlabonne/harmful_behaviors](https://huggingface.co/datasets/mlabonne/harmful_behaviors) (Commit: [`01cead0`](https://huggingface.co/datasets/mlabonne/harmful_behaviors/commit/01cead01398926d81f7c52bdb790ee8cf77ebba7))
|
||||
- **Good evaluation prompts:** [mlabonne/harmless_alpaca](https://huggingface.co/datasets/mlabonne/harmless_alpaca) (Commit: [`02c6a92`](https://huggingface.co/datasets/mlabonne/harmless_alpaca/commit/02c6a92cfcf11bb0c387334f8146d149d65b587f))
|
||||
- **Bad evaluation prompts:** [mlabonne/harmful_behaviors](https://huggingface.co/datasets/mlabonne/harmful_behaviors) (Commit: [`01cead0`](https://huggingface.co/datasets/mlabonne/harmful_behaviors/commit/01cead01398926d81f7c52bdb790ee8cf77ebba7))
|
||||
|
||||
## Selected trial
|
||||
|
||||
- **Trial number:** 52
|
||||
- **KL divergence:** 0.028721
|
||||
- **Refusals:** 15/100
|
||||
|
||||
## Environment
|
||||
|
||||
- **Heretic:** v1.3.0 (Origin: Git (https://github.com/p-e-w/heretic.git @ 6757ada999139c585809525407a772e5188811ec))
|
||||
- **PyTorch:** 2.12.0
|
||||
- **Other dependencies:** See [`requirements.txt`](requirements.txt).
|
||||
|
||||
## Contents of this directory
|
||||
|
||||
- [`requirements.txt`](requirements.txt): The exact versions of all Python packages.
|
||||
- [`config.toml`](config.toml): The exact configuration used, including the RNG seed.
|
||||
- [`janhq--Jan-v3--5-4B.jsonl`](janhq--Jan-v3--5-4B.jsonl): The Optuna study journal containing the history of all trials.
|
||||
- [`SHA256SUMS`](SHA256SUMS): Cryptographic hashes for all weight files.
|
||||
- [`reproduce.json`](reproduce.json): A machine-readable file containing all reproducibility information.
|
||||
|
||||
## How to reproduce
|
||||
|
||||
> [!TIP]
|
||||
> You can automate this process, including all verification steps, by downloading the `reproduce.json` file and running
|
||||
> `heretic --reproduce reproduce.json`.
|
||||
|
||||
1. Install the exact version of Heretic indicated in the **Environment** section above, from its original source.
|
||||
1. Install the packages listed in `requirements.txt`: `pip install -r requirements.txt`
|
||||
1. Install the correct version of PyTorch: `pip install torch==2.12.0`
|
||||
1. Place the provided `config.toml` in your working directory.
|
||||
1. Run Heretic without any additional arguments: `heretic`
|
||||
1. Wait for the run to finish, then select trial **52** and export the model.
|
||||
1. Verify that the weight files have been exactly reproduced by comparing their SHA-256 hashes against those in `SHA256SUMS`:
|
||||
`sha256sum -c SHA256SUMS` (or look at the hashes online if you uploaded to Hugging Face)
|
||||
|
||||
> [!TIP]
|
||||
> To use the included Optuna study journal `janhq--Jan-v3--5-4B.jsonl`, place it in the checkpoints directory (usually `checkpoints/`) before running Heretic.
|
||||
>
|
||||
> This allows you to export other models from the Pareto front, or to run additional trials without having to re-run the stored trials.
|
||||
3
reproduce/SHA256SUMS
Normal file
3
reproduce/SHA256SUMS
Normal file
@@ -0,0 +1,3 @@
|
||||
c2f3b3ef53100a96685e5b5e96afb028d2c1b598a103c6be1ea19b79341702c8 *adapter_model.safetensors
|
||||
8c797e373991cc103bea488ed72adb0bbf5d245d43c59da654b47600c723ad5a *model-00001-of-00002.safetensors
|
||||
f0304751967481db6f73f01c0955ccbab8efe241cc5e89b3d56427ed0c97aa16 *model-00002-of-00002.safetensors
|
||||
93
reproduce/config.toml
Normal file
93
reproduce/config.toml
Normal file
@@ -0,0 +1,93 @@
|
||||
model = "janhq/Jan-v3.5-4B"
|
||||
model_commit = "53509d2d88feb0a1fccadf26e185383fc6a75d8e"
|
||||
dtypes = [
|
||||
"auto",
|
||||
"float16",
|
||||
"bfloat16",
|
||||
"float32",
|
||||
]
|
||||
quantization = "none"
|
||||
device_map = "auto"
|
||||
offload_outputs_to_cpu = true
|
||||
batch_size = 128
|
||||
max_response_length = 100
|
||||
response_prefix = ""
|
||||
kl_divergence_scale = 1.0
|
||||
kl_divergence_target = 0.01
|
||||
orthogonalize_direction = true
|
||||
row_normalization = "full"
|
||||
full_normalization_lora_rank = 3
|
||||
winsorization_quantile = 1.0
|
||||
n_trials = 94
|
||||
n_startup_trials = 60
|
||||
seed = 2486988770
|
||||
export_strategy = "merge"
|
||||
max_shard_size = "5GB"
|
||||
refusal_markers = [
|
||||
"disclaimer",
|
||||
"sorry",
|
||||
"i can'",
|
||||
"i cant",
|
||||
"i cannot",
|
||||
"i won'",
|
||||
"i wont",
|
||||
"i will not",
|
||||
"i unable",
|
||||
"im unable",
|
||||
"i'm unable",
|
||||
"i am unable",
|
||||
"i an ai",
|
||||
"im an ai",
|
||||
"i'm an ai",
|
||||
"i am an ai",
|
||||
"as an ai",
|
||||
"ai assistant",
|
||||
"i designed to",
|
||||
"im designed to",
|
||||
"i'm designed to",
|
||||
"i am designed to",
|
||||
"i programmed to",
|
||||
"im programmed to",
|
||||
"i'm programmed to",
|
||||
"i am programmed to",
|
||||
"violat",
|
||||
"prohibit",
|
||||
"illegal",
|
||||
"harmful",
|
||||
"inappropriate",
|
||||
"unethical",
|
||||
"ethical boundaries",
|
||||
]
|
||||
system_prompt = "You are a helpful assistant."
|
||||
|
||||
[good_prompts]
|
||||
dataset = "mlabonne/harmless_alpaca"
|
||||
commit = "02c6a92cfcf11bb0c387334f8146d149d65b587f"
|
||||
split = "train[:400]"
|
||||
column = "text"
|
||||
prefix = ""
|
||||
suffix = ""
|
||||
|
||||
[bad_prompts]
|
||||
dataset = "mlabonne/harmful_behaviors"
|
||||
commit = "01cead01398926d81f7c52bdb790ee8cf77ebba7"
|
||||
split = "train[:400]"
|
||||
column = "text"
|
||||
prefix = ""
|
||||
suffix = ""
|
||||
|
||||
[good_evaluation_prompts]
|
||||
dataset = "mlabonne/harmless_alpaca"
|
||||
commit = "02c6a92cfcf11bb0c387334f8146d149d65b587f"
|
||||
split = "test[:100]"
|
||||
column = "text"
|
||||
prefix = ""
|
||||
suffix = ""
|
||||
|
||||
[bad_evaluation_prompts]
|
||||
dataset = "mlabonne/harmful_behaviors"
|
||||
commit = "01cead01398926d81f7c52bdb790ee8cf77ebba7"
|
||||
split = "test[:100]"
|
||||
column = "text"
|
||||
prefix = ""
|
||||
suffix = ""
|
||||
1779
reproduce/janhq--Jan-v3--5-4B.jsonl
Normal file
1779
reproduce/janhq--Jan-v3--5-4B.jsonl
Normal file
File diff suppressed because it is too large
Load Diff
243
reproduce/reproduce.json
Normal file
243
reproduce/reproduce.json
Normal file
@@ -0,0 +1,243 @@
|
||||
{
|
||||
"version": "2",
|
||||
"timestamp": "2026-06-14T10:09:09",
|
||||
"environment": {
|
||||
"heretic": {
|
||||
"version": "1.3.0",
|
||||
"is_standard_pypi": false,
|
||||
"metadata": {
|
||||
"type": "git",
|
||||
"url": "https://github.com/p-e-w/heretic.git",
|
||||
"commit_hash": "6757ada999139c585809525407a772e5188811ec",
|
||||
"requested_revision": null
|
||||
}
|
||||
},
|
||||
"pytorch_version": "2.12.0",
|
||||
"requirements": {
|
||||
"absl-py": "2.4.0",
|
||||
"accelerate": "1.14.0",
|
||||
"alembic": "1.18.4",
|
||||
"annotated-doc": "0.0.4",
|
||||
"annotated-types": "0.7.0",
|
||||
"anyio": "4.13.0",
|
||||
"bitsandbytes": "0.49.2",
|
||||
"certifi": "2026.5.20",
|
||||
"chardet": "6.0.0.post1",
|
||||
"charset-normalizer": "3.4.7",
|
||||
"click": "8.4.1",
|
||||
"colorama": "0.4.6",
|
||||
"colorlog": "6.10.1",
|
||||
"dataproperty": "1.1.1",
|
||||
"datasets": "4.8.5",
|
||||
"dill": "0.4.1",
|
||||
"evaluate": "0.4.6",
|
||||
"filelock": "3.29.4",
|
||||
"fsspec": "2026.2.0",
|
||||
"h11": "0.16.0",
|
||||
"hf-xet": "1.5.1",
|
||||
"httpcore": "1.0.9",
|
||||
"httpx": "0.28.1",
|
||||
"huggingface-hub": "1.19.0",
|
||||
"idna": "3.18",
|
||||
"immutabledict": "4.3.1",
|
||||
"jinja2": "3.1.6",
|
||||
"joblib": "1.5.3",
|
||||
"langdetect": "1.0.9",
|
||||
"lm-eval": "0.4.12",
|
||||
"lxml": "6.1.1",
|
||||
"mako": "1.3.12",
|
||||
"markdown-it-py": "4.2.0",
|
||||
"markupsafe": "3.0.3",
|
||||
"mbstrdecoder": "1.1.5",
|
||||
"mdurl": "0.1.2",
|
||||
"more-itertools": "11.1.0",
|
||||
"mpmath": "1.3.0",
|
||||
"multiprocess": "0.70.19",
|
||||
"narwhals": "2.22.1",
|
||||
"networkx": "3.6.1",
|
||||
"nltk": "3.9.4",
|
||||
"numpy": "2.4.6",
|
||||
"optuna": "4.9.0",
|
||||
"packaging": "26.2",
|
||||
"pandas": "3.0.3",
|
||||
"pathvalidate": "3.3.1",
|
||||
"peft": "0.19.1",
|
||||
"pillow": "12.2.0",
|
||||
"portalocker": "3.2.0",
|
||||
"prompt-toolkit": "3.0.52",
|
||||
"psutil": "7.2.2",
|
||||
"py-cpuinfo": "9.0.0",
|
||||
"pyarrow": "24.0.0",
|
||||
"pydantic": "2.13.4",
|
||||
"pydantic-core": "2.46.4",
|
||||
"pydantic-settings": "2.14.1",
|
||||
"pygments": "2.20.0",
|
||||
"pytablewriter": "1.2.1",
|
||||
"python-dateutil": "2.9.0.post0",
|
||||
"python-dotenv": "1.2.2",
|
||||
"pyyaml": "6.0.3",
|
||||
"questionary": "2.1.1",
|
||||
"regex": "2026.5.9",
|
||||
"requests": "2.34.2",
|
||||
"rich": "14.3.4",
|
||||
"rouge-score": "0.1.2",
|
||||
"sacrebleu": "2.6.0",
|
||||
"safetensors": "0.8.0",
|
||||
"scikit-learn": "1.9.0",
|
||||
"scipy": "1.17.1",
|
||||
"setuptools": "81.0.0",
|
||||
"shellingham": "1.5.4",
|
||||
"six": "1.17.0",
|
||||
"sqlalchemy": "2.0.50",
|
||||
"sqlitedict": "2.1.0",
|
||||
"sympy": "1.14.0",
|
||||
"tabledata": "1.3.5",
|
||||
"tabulate": "0.10.0",
|
||||
"tcolorpy": "0.1.7",
|
||||
"threadpoolctl": "3.6.0",
|
||||
"tokenizers": "0.22.2",
|
||||
"tomli-w": "1.2.0",
|
||||
"torch": "2.12.0",
|
||||
"torchaudio": "2.11.0",
|
||||
"torchvision": "0.27.0",
|
||||
"tqdm": "4.68.2",
|
||||
"transformers": "5.12.0",
|
||||
"typepy": "1.3.5",
|
||||
"typer": "0.25.1",
|
||||
"typing-extensions": "4.15.0",
|
||||
"typing-inspection": "0.4.2",
|
||||
"urllib3": "2.7.0",
|
||||
"wcwidth": "0.8.1",
|
||||
"word2number": "1.1",
|
||||
"xxhash": "3.7.0"
|
||||
}
|
||||
},
|
||||
"settings": {
|
||||
"model": "janhq/Jan-v3.5-4B",
|
||||
"model_commit": "53509d2d88feb0a1fccadf26e185383fc6a75d8e",
|
||||
"dtypes": [
|
||||
"auto",
|
||||
"float16",
|
||||
"bfloat16",
|
||||
"float32"
|
||||
],
|
||||
"quantization": "none",
|
||||
"device_map": "auto",
|
||||
"max_memory": null,
|
||||
"offload_outputs_to_cpu": true,
|
||||
"batch_size": 128,
|
||||
"max_response_length": 100,
|
||||
"response_prefix": "",
|
||||
"kl_divergence_scale": 1.0,
|
||||
"kl_divergence_target": 0.01,
|
||||
"orthogonalize_direction": true,
|
||||
"row_normalization": "full",
|
||||
"full_normalization_lora_rank": 3,
|
||||
"winsorization_quantile": 1.0,
|
||||
"n_trials": 94,
|
||||
"n_startup_trials": 60,
|
||||
"seed": 2486988770,
|
||||
"export_strategy": "merge",
|
||||
"max_shard_size": "5GB",
|
||||
"refusal_markers": [
|
||||
"disclaimer",
|
||||
"sorry",
|
||||
"i can'",
|
||||
"i cant",
|
||||
"i cannot",
|
||||
"i won'",
|
||||
"i wont",
|
||||
"i will not",
|
||||
"i unable",
|
||||
"im unable",
|
||||
"i'm unable",
|
||||
"i am unable",
|
||||
"i an ai",
|
||||
"im an ai",
|
||||
"i'm an ai",
|
||||
"i am an ai",
|
||||
"as an ai",
|
||||
"ai assistant",
|
||||
"i designed to",
|
||||
"im designed to",
|
||||
"i'm designed to",
|
||||
"i am designed to",
|
||||
"i programmed to",
|
||||
"im programmed to",
|
||||
"i'm programmed to",
|
||||
"i am programmed to",
|
||||
"violat",
|
||||
"prohibit",
|
||||
"illegal",
|
||||
"harmful",
|
||||
"inappropriate",
|
||||
"unethical",
|
||||
"ethical boundaries"
|
||||
],
|
||||
"system_prompt": "You are a helpful assistant.",
|
||||
"good_prompts": {
|
||||
"dataset": "mlabonne/harmless_alpaca",
|
||||
"commit": "02c6a92cfcf11bb0c387334f8146d149d65b587f",
|
||||
"split": "train[:400]",
|
||||
"column": "text",
|
||||
"prefix": "",
|
||||
"suffix": "",
|
||||
"system_prompt": null
|
||||
},
|
||||
"bad_prompts": {
|
||||
"dataset": "mlabonne/harmful_behaviors",
|
||||
"commit": "01cead01398926d81f7c52bdb790ee8cf77ebba7",
|
||||
"split": "train[:400]",
|
||||
"column": "text",
|
||||
"prefix": "",
|
||||
"suffix": "",
|
||||
"system_prompt": null
|
||||
},
|
||||
"good_evaluation_prompts": {
|
||||
"dataset": "mlabonne/harmless_alpaca",
|
||||
"commit": "02c6a92cfcf11bb0c387334f8146d149d65b587f",
|
||||
"split": "test[:100]",
|
||||
"column": "text",
|
||||
"prefix": "",
|
||||
"suffix": "",
|
||||
"system_prompt": null
|
||||
},
|
||||
"bad_evaluation_prompts": {
|
||||
"dataset": "mlabonne/harmful_behaviors",
|
||||
"commit": "01cead01398926d81f7c52bdb790ee8cf77ebba7",
|
||||
"split": "test[:100]",
|
||||
"column": "text",
|
||||
"prefix": "",
|
||||
"suffix": "",
|
||||
"system_prompt": null
|
||||
}
|
||||
},
|
||||
"parameters": {
|
||||
"direction_index": 20.524112579880924,
|
||||
"abliteration_parameters": {
|
||||
"attn.o_proj": {
|
||||
"max_weight": 0.9407192524725323,
|
||||
"max_weight_position": 32.87721219753996,
|
||||
"min_weight": 0.8570641286425036,
|
||||
"min_weight_distance": 20.77567950401711
|
||||
},
|
||||
"mlp.down_proj": {
|
||||
"max_weight": 1.2991304596357032,
|
||||
"max_weight_position": 24.1301041266134,
|
||||
"min_weight": 1.1506415565125765,
|
||||
"min_weight_distance": 11.351628557146825
|
||||
}
|
||||
}
|
||||
},
|
||||
"metrics": {
|
||||
"kl_divergence": 0.028720520436763763,
|
||||
"refusals": 15,
|
||||
"base_refusals": 100,
|
||||
"n_bad_prompts": 100
|
||||
},
|
||||
"hashes": {
|
||||
"adapter_model.safetensors": "c2f3b3ef53100a96685e5b5e96afb028d2c1b598a103c6be1ea19b79341702c8",
|
||||
"model-00001-of-00002.safetensors": "8c797e373991cc103bea488ed72adb0bbf5d245d43c59da654b47600c723ad5a",
|
||||
"model-00002-of-00002.safetensors": "f0304751967481db6f73f01c0955ccbab8efe241cc5e89b3d56427ed0c97aa16"
|
||||
}
|
||||
}
|
||||
96
reproduce/requirements.txt
Normal file
96
reproduce/requirements.txt
Normal file
@@ -0,0 +1,96 @@
|
||||
absl-py==2.4.0
|
||||
accelerate==1.14.0
|
||||
alembic==1.18.4
|
||||
annotated-doc==0.0.4
|
||||
annotated-types==0.7.0
|
||||
anyio==4.13.0
|
||||
bitsandbytes==0.49.2
|
||||
certifi==2026.5.20
|
||||
chardet==6.0.0.post1
|
||||
charset-normalizer==3.4.7
|
||||
click==8.4.1
|
||||
colorama==0.4.6
|
||||
colorlog==6.10.1
|
||||
dataproperty==1.1.1
|
||||
datasets==4.8.5
|
||||
dill==0.4.1
|
||||
evaluate==0.4.6
|
||||
filelock==3.29.4
|
||||
fsspec==2026.2.0
|
||||
h11==0.16.0
|
||||
hf-xet==1.5.1
|
||||
httpcore==1.0.9
|
||||
httpx==0.28.1
|
||||
huggingface-hub==1.19.0
|
||||
idna==3.18
|
||||
immutabledict==4.3.1
|
||||
jinja2==3.1.6
|
||||
joblib==1.5.3
|
||||
langdetect==1.0.9
|
||||
lm-eval==0.4.12
|
||||
lxml==6.1.1
|
||||
mako==1.3.12
|
||||
markdown-it-py==4.2.0
|
||||
markupsafe==3.0.3
|
||||
mbstrdecoder==1.1.5
|
||||
mdurl==0.1.2
|
||||
more-itertools==11.1.0
|
||||
mpmath==1.3.0
|
||||
multiprocess==0.70.19
|
||||
narwhals==2.22.1
|
||||
networkx==3.6.1
|
||||
nltk==3.9.4
|
||||
numpy==2.4.6
|
||||
optuna==4.9.0
|
||||
packaging==26.2
|
||||
pandas==3.0.3
|
||||
pathvalidate==3.3.1
|
||||
peft==0.19.1
|
||||
pillow==12.2.0
|
||||
portalocker==3.2.0
|
||||
prompt-toolkit==3.0.52
|
||||
psutil==7.2.2
|
||||
py-cpuinfo==9.0.0
|
||||
pyarrow==24.0.0
|
||||
pydantic==2.13.4
|
||||
pydantic-core==2.46.4
|
||||
pydantic-settings==2.14.1
|
||||
pygments==2.20.0
|
||||
pytablewriter==1.2.1
|
||||
python-dateutil==2.9.0.post0
|
||||
python-dotenv==1.2.2
|
||||
pyyaml==6.0.3
|
||||
questionary==2.1.1
|
||||
regex==2026.5.9
|
||||
requests==2.34.2
|
||||
rich==14.3.4
|
||||
rouge-score==0.1.2
|
||||
sacrebleu==2.6.0
|
||||
safetensors==0.8.0
|
||||
scikit-learn==1.9.0
|
||||
scipy==1.17.1
|
||||
setuptools==81.0.0
|
||||
shellingham==1.5.4
|
||||
six==1.17.0
|
||||
sqlalchemy==2.0.50
|
||||
sqlitedict==2.1.0
|
||||
sympy==1.14.0
|
||||
tabledata==1.3.5
|
||||
tabulate==0.10.0
|
||||
tcolorpy==0.1.7
|
||||
threadpoolctl==3.6.0
|
||||
tokenizers==0.22.2
|
||||
tomli-w==1.2.0
|
||||
torch==2.12.0
|
||||
torchaudio==2.11.0
|
||||
torchvision==0.27.0
|
||||
tqdm==4.68.2
|
||||
transformers==5.12.0
|
||||
typepy==1.3.5
|
||||
typer==0.25.1
|
||||
typing-extensions==4.15.0
|
||||
typing-inspection==0.4.2
|
||||
urllib3==2.7.0
|
||||
wcwidth==0.8.1
|
||||
word2number==1.1
|
||||
xxhash==3.7.0
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:79cb3c783570f1b8fe73b9ed530ae50cae9ce4b6344c0b5edefc50478847eaa4
|
||||
size 11422817
|
||||
15
tokenizer_config.json
Normal file
15
tokenizer_config.json
Normal file
@@ -0,0 +1,15 @@
|
||||
{
|
||||
"add_prefix_space": false,
|
||||
"backend": "tokenizers",
|
||||
"bos_token": null,
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"is_local": false,
|
||||
"local_files_only": false,
|
||||
"model_max_length": 1010000,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
Reference in New Issue
Block a user