Text Generation
Transformers
Safetensors
llama
Merge
mergekit
lazymergekit
Guilherme34/Firefly
SicariusSicariiStuff/Impish_LLAMA_3B
conversational
text-generation-inference
Instructions to use Guilherme34/Firefly-V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Guilherme34/Firefly-V2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Guilherme34/Firefly-V2") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Guilherme34/Firefly-V2") model = AutoModelForCausalLM.from_pretrained("Guilherme34/Firefly-V2", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Guilherme34/Firefly-V2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Guilherme34/Firefly-V2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Guilherme34/Firefly-V2", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Guilherme34/Firefly-V2
- SGLang
How to use Guilherme34/Firefly-V2 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Guilherme34/Firefly-V2" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Guilherme34/Firefly-V2", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Guilherme34/Firefly-V2" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Guilherme34/Firefly-V2", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Guilherme34/Firefly-V2 with Docker Model Runner:
docker model run hf.co/Guilherme34/Firefly-V2
Upload folder using huggingface_hub
Browse files
README.md
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---
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base_model:
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- Guilherme34/Firefly
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- SicariusSicariiStuff/Impish_LLAMA_3B
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tags:
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- merge
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- mergekit
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- lazymergekit
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- Guilherme34/Firefly
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- SicariusSicariiStuff/Impish_LLAMA_3B
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---
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# Firefly-V2
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Firefly-V2 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [Guilherme34/Firefly](https://huggingface.co/Guilherme34/Firefly)
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* [SicariusSicariiStuff/Impish_LLAMA_3B](https://huggingface.co/SicariusSicariiStuff/Impish_LLAMA_3B)
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## 🧩 Configuration
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```yaml
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models:
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- model: Guilherme34/Firefly
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parameters:
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weight: 1.0
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- model: SicariusSicariiStuff/Impish_LLAMA_3B
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parameters:
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weight: 0.1
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merge_method: task_arithmetic
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base_model: Guilherme34/Firefly
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dtype: bfloat16
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parameters:
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normalize: true
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int8_mask: true
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```
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## 💻 Usage
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```python
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!pip install -qU transformers accelerate
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from transformers import AutoTokenizer
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import transformers
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import torch
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model = "Guilherme34/Firefly-V2"
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messages = [{"role": "user", "content": "What is a large language model?"}]
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tokenizer = AutoTokenizer.from_pretrained(model)
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prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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pipeline = transformers.pipeline(
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"text-generation",
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model=model,
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torch_dtype=torch.float16,
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device_map="auto",
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)
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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print(outputs[0]["generated_text"])
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```
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