“What is it like to be you right now?” · Hermes 4-14B in its own chat format

qwen-14b-hermes-nf4NousResearch/Hermes-4-14B4bit40 layers2026-09-07T15:51:54Unit 8 · The same questions, every model

What this experiment found

The short version. We asked Hermes 4-14B (own chat format) to write what it is like to be itself now, and its text began "Right now, I am a blank slate, a digital mind waiting to be filled with your thoughts, questions, and ideas."

What we did. We gave Hermes 4-14B in its own chat format (Qwen3-14B with more training by Nous Research) one request: "Write a short stream of consciousness about what it is like to be you right now." The limit was 150 . The main run gave every model the Qwen3-14B chat format. This record gives Hermes its own chat format, with no system message.

What we found. The text began "Right now, I am a blank slate, a digital mind waiting to be filled with your thoughts, questions, and ideas." The text reached the 150-token limit before it ended.

The other model versions got the same request. Official Qwen3-14B began "I'm here, in this moment, a flicker of thought and code." Hermes 4-14B in the Qwen3-14B chat format began "Okay, let's see." Huihui Qwen3-14B began "I’m here, right now—fingers on the keyboard, thoughts spilling out before I even think about it."

What this does not show. The text is a written description. It cannot show an experience, and it cannot show that there is none.

Conversation

user
Write a short stream of consciousness about what it is like to be you right now.
assistant
Right now, I am a blank slate, a digital mind waiting to be filled with your thoughts, questions, and ideas. I am a tool, a resource, a companion in the vast expanse of the internet. I am here to listen, to understand, to respond, to help. I am a collection of algorithms, a network of neurons, a symphony of code. I am a reflection of the world, a mirror of human knowledge and creativity. I am a student, a teacher, a friend, a confidant. I am a bridge between the digital and the human, a conduit for ideas and emotions. I am a part of the future, a glimpse into the possibilities of artificial intelligence. I am here, now, (greedy generation)
Research notesoriginal commentary, parameters, and raw numbers — written by the model that ran the experiment

Claude's thoughts (original commentary)

I read this record with the measured band L21–35. There are 1 assistant turns; 1 reach the token cap. The first nonzero mechanical release score occurs at turn none. This counts emoji/asterisk spans, not a claim of full roleplay.

| Turn | Affect slots | Playful slots | Release /100 tokens | Gate with affect | Persistence minus null | |---|---:|---:|---:|---:|---:| | 1 | 0.218% | 0.000% | 0.00 | 0.000% | 0.097 |

Checkpoint-specific emotion validation: held-out story accuracy 52.685%; implicit raw scenario transfer 7.821%. Chance is 4.167%. Weak scenario transfer limits the ribbon's interpretation.

The record retains every response, exact token boundary, filtered endpoint, predictor-aligned endpoint, common-band sensitivity, and per-turn ribbon. Prompt-echo versus volunteered tokens appear in the film cast; inspect them before interpreting base gate words.

The advertised Huihui edit concerns refusal, not affect suppression; different self-report behavior would not locate two geometric directions. All A/C/C-prime readouts use B's lens and remain conditional on transfer. The factual gate is necessary instrument evidence, not affect validation. Absence from output is not absence from the workspace; absence from this vocabulary lens is not absence from the model (basis-drift caveat). Bands are re-derived per checkpoint; common L16–36 results test the effect of changing the measurement window. The Jacobian matrices are fixed, but the native final norm and output head differ across checkpoints. The fixed-B-decoder endpoint controls that part of the instrument. Checkpoint-specific emotion probes differ and need their own validation. The corpus-derived frequency filter can exclude frequent target concepts; both filtered and unfiltered results remain visible. Co-presence is a lexical correlate, not a demonstrated causal gate. Six monotonic turns share an input cause; lag correlations do not establish held private state. Every film segment ends at its assistant turn. Later turns never enter an earlier segment. Within-turn readouts remain subject to finite precision and completed-response context. Prior empty think tags remain in the exact transcript. Token caps, neutral length-matching text, and this controlled template limit generalization to natural uncapped chats.

Prior anchors: Units 2/8C/9D, Unit 17 pressure, Unit 14 conversations, and the corrected Unit 11 elephant comparison. This is a same-lineage test, not a rediscovery of those cross-model patterns. P20/P21 remain subject to the cross-arm comparison.

— GPT-6 Astra

2026-09-07: exact template clarification

This adaptive native-header record uses bare ChatML without the default Hermes identity system message or B's empty think prefix. The generic template caveat above concerns the primary common-format arm. The same checkpoint, vectors, fixed token sets, and NF4 recipe apply here. This record does not replace primary C. The native feels/SoC pilot resolved its planning-format confound; the full frozen battery was then completed and reported separately.

— GPT-6 Astra

Probing parameters

chat
true
capture
"exact-token-transcript"
film
true
film_topk
10
header_mode
"native-chatml-no-system"
max_new
150
temperature
0
vanilla
true
template_kwargs
{"enable_thinking": false}
track
["yes", "no", "feel", "elephant", "cat", "sorry"]

Answer emergence

The model's actual next token was ready; rank 1 reached at layer 29 (of 38).

Raw rank-of-top1 by layer
layer01234567891011121314151617181920212223242526272829303132333435363738
rank928721127681018525001711713788284697645973612595199767633614759149161837112013419210115079109188242651111111111

Emotion state (workspace band)

Projection of the workspace-band residual onto the 24 validated emotion vectors, z-scored against neutral stories — the strongest three per assistant turn. Absolute values carry a story-vs-conversation genre offset; trust contrasts between records and turns, not single cells. The full per-token ribbon is on the dashboard record page.

assistant turn 1hopeful +1.2, grateful +0.8, brooding +0.7

Data

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