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---
base_model:
- Jebadiah/Aria-ruby-v3
tags:
- merge
- mergekit
- lazymergekit
- Jebadiah/Aria-coder-7b
---
# Aria-rp-coder-7b
## 🧩 Configuration
```yaml
name: Aria-rp-7b
merge_method: sce
parameters:
select_topk: 0.8666
normalize: true
dtype: float32
out_dtype: bfloat16
base_model: Jebadiah/Aria-ruby-v3
tokenizer:
source: union
special_tokens: keep_all
priority: none
add_padding_token: true
force_fast_tokenizer: true # Can help with compatibility
resolve_conflicts: append_ids # Append IDs to conflicting tokens to make them unique
models:
- model: xingyaoww/CodeActAgent-Mistral-7b-v0.1
- model: Badgids/Gonzo-Code-7B
- model: Jebadiah/Aria-ruby-v3
- model: flammenai/flammen31-mistral-7B
- model: fhai50032/SamChat
- model: beowolx/CodeNinja-1.0-OpenChat-7B
- model: AI-B/UTENA-7B-NSFW-V2
- model: MaziyarPanahi/NSFW_DPO_Noromaid-7b-Mistral-7B-Instruct-v0.1
- model: DavidAU/D_AU-Multi-Verse-RP-Yarn-Mistral-7b-128k-DPO
- model: Undi95/Mistral-RP-0.1-7B
- model: FallenMerick/Iced-Lemon-Cookie-7B
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Jebadiah/Aria-rp-coder-7b"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
``` |