Text Generation
Transformers
Safetensors
qwen2
llama-factory
full
Generated from Trainer
conversational
text-generation-inference
Instructions to use mlfoundations-dev/a1_code_react with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlfoundations-dev/a1_code_react with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="mlfoundations-dev/a1_code_react") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("mlfoundations-dev/a1_code_react") model = AutoModelForCausalLM.from_pretrained("mlfoundations-dev/a1_code_react") 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]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use mlfoundations-dev/a1_code_react with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "mlfoundations-dev/a1_code_react" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mlfoundations-dev/a1_code_react", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/mlfoundations-dev/a1_code_react
- SGLang
How to use mlfoundations-dev/a1_code_react 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 "mlfoundations-dev/a1_code_react" \ --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": "mlfoundations-dev/a1_code_react", "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 "mlfoundations-dev/a1_code_react" \ --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": "mlfoundations-dev/a1_code_react", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use mlfoundations-dev/a1_code_react with Docker Model Runner:
docker model run hf.co/mlfoundations-dev/a1_code_react
| assistant_tag: gpt | |
| bf16: 'True' | |
| content_tag: value | |
| cutoff_len: '16384' | |
| dataloader_num_workers: '4' | |
| dataloader_persistent_workers: 'True' | |
| dataloader_pin_memory: 'True' | |
| dataset: mlfoundations-dev/a1_code_react | |
| dataset_dir: ONLINE | |
| ddp_timeout: '180000000' | |
| deepspeed: /opt/ml/code/zero3.json | |
| do_train: 'True' | |
| enable_liger_kernel: 'True' | |
| finetuning_type: full | |
| formatting: sharegpt | |
| global_batch_size: '128' | |
| gradient_accumulation_steps: '16' | |
| hub_model_id: mlfoundations-dev/a1_code_react | |
| learning_rate: 4e-05 | |
| logging_steps: '1' | |
| lr_scheduler_type: cosine | |
| messages: conversations | |
| model_name_or_path: Qwen/Qwen2.5-7B-Instruct | |
| num_train_epochs: '5.0' | |
| output_dir: /opt/ml/model | |
| overwrite_cache: 'True' | |
| per_device_train_batch_size: '1' | |
| plot_loss: 'True' | |
| preprocessing_num_workers: '16' | |
| push_to_db: 'True' | |
| push_to_hub: 'True' | |
| report_to: wandb | |
| role_tag: from | |
| run_name: a1_code_react | |
| save_strategy: epoch | |
| stage: sft | |
| template: qwen25 | |
| user_tag: human | |
| warmup_ratio: '0.1' | |