56 lines
1.3 KiB
Markdown
56 lines
1.3 KiB
Markdown
|
---
|
||
|
|
license: apache-2.0
|
||
|
|
base_model: Qwen/Qwen3-4B-Instruct-2507
|
||
|
|
language:
|
||
|
|
- en
|
||
|
|
pipeline_tag: text-generation
|
||
|
|
library_name: transformers
|
||
|
|
tags:
|
||
|
|
- qwen3
|
||
|
|
- instruct
|
||
|
|
- conversational
|
||
|
|
---
|
||
|
|
|
||
|
|
# fable-traces
|
||
|
|
|
||
|
|
A compact instruction-tuned language model built on
|
||
|
|
[Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507).
|
||
|
|
`fable-traces` is tuned for short, conversational replies and runs comfortably on a
|
||
|
|
single mid-range GPU.
|
||
|
|
|
||
|
|
## Usage
|
||
|
|
|
||
|
|
```python
|
||
|
|
from transformers import AutoModelForCausalLM, AutoTokenizer
|
||
|
|
import torch
|
||
|
|
|
||
|
|
repo = "AliesTaha/fable-traces"
|
||
|
|
tok = AutoTokenizer.from_pretrained(repo)
|
||
|
|
model = AutoModelForCausalLM.from_pretrained(repo, dtype=torch.bfloat16, device_map="auto")
|
||
|
|
|
||
|
|
messages = [{"role": "user", "content": "Tell me something interesting."}]
|
||
|
|
ids = tok.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device)
|
||
|
|
out = model.generate(ids, max_new_tokens=100, do_sample=False)
|
||
|
|
print(tok.decode(out[0, ids.shape[1]:], skip_special_tokens=True))
|
||
|
|
```
|
||
|
|
|
||
|
|
Serve with vLLM:
|
||
|
|
|
||
|
|
```bash
|
||
|
|
vllm serve AliesTaha/fable-traces
|
||
|
|
```
|
||
|
|
|
||
|
|
## Details
|
||
|
|
|
||
|
|
| | |
|
||
|
|
|---|---|
|
||
|
|
| Base model | Qwen3-4B-Instruct-2507 |
|
||
|
|
| Parameters | ~4B |
|
||
|
|
| Precision | bfloat16 (safetensors) |
|
||
|
|
| Prompt format | ChatML — use the tokenizer's chat template |
|
||
|
|
| Context length | inherits the base model |
|
||
|
|
|
||
|
|
## License
|
||
|
|
|
||
|
|
Apache 2.0, following the base model.
|