Files
HumanPet-X1-1.7B-GGUF/README.md
ModelHub XC 0458d965ce 初始化项目,由ModelHub XC社区提供模型
Model: Flexan/HumanPet-X1-1.7B-GGUF
Source: Original Platform
2026-06-13 17:59:17 +08:00

96 lines
4.3 KiB
Markdown

---
license: cc-by-sa-4.0
datasets:
- ConvLab/dailydialog
language:
- en
base_model: Flexan/HumanPet-X1-1.7B
pipeline_tag: text-generation
new_version: Flexan/HumanPet-X2.2-1.7B-GGUF
---
# GGUF Files for HumanPet-X1-1.7B
These are the GGUF files for [Flexan/HumanPet-X1-1.7B](https://huggingface.co/Flexan/HumanPet-X1-1.7B).
## Downloads
| GGUF Link | Quantization | Description |
| ---- | ----- | ----------- |
| [Download](https://huggingface.co/Flexan/HumanPet-X1-1.7B-GGUF/resolve/main/HumanPet-X1-1.7B.Q2_K.gguf) | Q2_K | Lowest quality |
| [Download](https://huggingface.co/Flexan/HumanPet-X1-1.7B-GGUF/resolve/main/HumanPet-X1-1.7B.Q3_K_S.gguf) | Q3_K_S | |
| [Download](https://huggingface.co/Flexan/HumanPet-X1-1.7B-GGUF/resolve/main/HumanPet-X1-1.7B.IQ3_S.gguf) | IQ3_S | Integer quant, preferable over Q3_K_S |
| [Download](https://huggingface.co/Flexan/HumanPet-X1-1.7B-GGUF/resolve/main/HumanPet-X1-1.7B.IQ3_M.gguf) | IQ3_M | Integer quant |
| [Download](https://huggingface.co/Flexan/HumanPet-X1-1.7B-GGUF/resolve/main/HumanPet-X1-1.7B.Q3_K_M.gguf) | Q3_K_M | |
| [Download](https://huggingface.co/Flexan/HumanPet-X1-1.7B-GGUF/resolve/main/HumanPet-X1-1.7B.Q3_K_L.gguf) | Q3_K_L | |
| [Download](https://huggingface.co/Flexan/HumanPet-X1-1.7B-GGUF/resolve/main/HumanPet-X1-1.7B.IQ4_XS.gguf) | IQ4_XS | Integer quant |
| [Download](https://huggingface.co/Flexan/HumanPet-X1-1.7B-GGUF/resolve/main/HumanPet-X1-1.7B.Q4_K_S.gguf) | Q4_K_S | Fast with good performance |
| [Download](https://huggingface.co/Flexan/HumanPet-X1-1.7B-GGUF/resolve/main/HumanPet-X1-1.7B.Q4_K_M.gguf) | Q4_K_M | **Recommended:** Perfect mix of speed and performance |
| [Download](https://huggingface.co/Flexan/HumanPet-X1-1.7B-GGUF/resolve/main/HumanPet-X1-1.7B.Q5_K_S.gguf) | Q5_K_S | |
| [Download](https://huggingface.co/Flexan/HumanPet-X1-1.7B-GGUF/resolve/main/HumanPet-X1-1.7B.Q5_K_M.gguf) | Q5_K_M | |
| [Download](https://huggingface.co/Flexan/HumanPet-X1-1.7B-GGUF/resolve/main/HumanPet-X1-1.7B.Q6_K.gguf) | Q6_K | Very good quality |
| [Download](https://huggingface.co/Flexan/HumanPet-X1-1.7B-GGUF/resolve/main/HumanPet-X1-1.7B.Q8_0.gguf) | Q8_0 | Best quality |
| [Download](https://huggingface.co/Flexan/HumanPet-X1-1.7B-GGUF/resolve/main/HumanPet-X1-1.7B.f16.gguf) | f16 | Full precision, don't bother; use a quant |
# HumanPet X1 1.7B
## Description
HumanPet X1 1.7B is an instruct LLM consisting of 1.7B parameters trained to talk in a human conversational manner. It does not support reasoning nor tool-calling (although the base model does).
The model was LoRA fine-tuned with [Qwen/Qwen3-1.7B](https://huggingface.co/Qwen/Qwen3-1.7B) as base model.
The HumanPet series is part of an experiment. Do not expect consistent releases.
[Explanation of the experiment](https://huggingface.co/Flexan/HumanPet)
[Progress on the experiment](https://huggingface.co/Flexan/HumanPet#progress)
[Findings for HumanPet X1 1.7B](https://huggingface.co/Flexan/HumanPet#humanpet-x1-17b)
> [!NOTE]
> **Note:** the model files are **not released yet.** [Read section 'Stages' in the experiment explanation.](https://huggingface.co/Flexan/HumanPet#stages)
## Chat Format
HumanPet X1 1.7B uses the ChatML format, e.g.:
```text
<|im_start|>system
System message<|im_end|>
<|im_start|>user
User prompt<|im_end|>
<|im_start|>assistant
Assistant response<|im_end|>
```
## Usage
This model is not trained on system prompts. Therefore, it is recommended to not send any system messages. This includes tools (which this model also was not trained on).
The assistant response has the following format:
```text
<|im_start|>assistant
<think>
</think>
What happened?
<extra>
{"intent": "question", "emotion": "no emotion"}
</extra><|im_end|>
```
Note that the `<think>...</think>` tags are always empty, as this model was not trained on reasoning data.
The `<extra>...</extra>` tags contain JSON data of this schema:
```ts
{
intent: "directive" | "commissive" | "question" | "inform",
emotion: "no emotion" | "happiness" | "surprise" | "fear" | "disgust" | "sadness" | "anger"
}
```
If the model does not adhere to this schema, please let us know in the community tab.
## Datasets
1. **[ConvLab/dailydialog](https://huggingface.co/datasets/ConvLab/dailydialog)** *4.3k chats*
Only the conversations from the "Relationship" domain have been used.