README.md

metadata

tags:
  - merge
  - mergekit
  - lazymergekit
  - yuiseki/tinyllama-coder-sql-en-v0.1
  - TinyLlama/TinyLlama-1.1B-Chat-v1.0
base_model:
  - yuiseki/tinyllama-coder-sql-en-v0.1
  - TinyLlama/TinyLlama-1.1B-Chat-v1.0

chat-sql

chat-sql is a merge of the following models using LazyMergekit:

• yuiseki/tinyllama-coder-sql-en-v0.1
• TinyLlama/TinyLlama-1.1B-Chat-v1.0

🧩 Configuration

slices:
  - sources:
      - model: yuiseki/tinyllama-coder-sql-en-v0.1
        layer_range: [0, 22]
      - model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
        layer_range: [0, 22]
merge_method: slerp
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
parameters:
  t:
    - filter: lm_head
      value: [0.75]
    - filter: embed_tokens
      value: [0.75]
    - filter: self_attn
      value: [0.75,0.25]
    - filter: mlp
      value: [0.25,0.75]
    - filter: layernorm
      value: [0.5,0.5]
    - filter: modelnorm
      value: [0.75]
    - value: 0.5
dtype: bfloat16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "ajay141/chat-sql"
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"])