Text Generation
Transformers
TensorBoard
Safetensors
gemma3_text
Generated from Trainer
sft
trl
conversational
text-generation-inference
Instructions to use TanishkB/RandomNumberGenerator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TanishkB/RandomNumberGenerator with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TanishkB/RandomNumberGenerator") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("TanishkB/RandomNumberGenerator") model = AutoModelForCausalLM.from_pretrained("TanishkB/RandomNumberGenerator", 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=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use TanishkB/RandomNumberGenerator with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TanishkB/RandomNumberGenerator" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TanishkB/RandomNumberGenerator", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/TanishkB/RandomNumberGenerator
- SGLang
How to use TanishkB/RandomNumberGenerator 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 "TanishkB/RandomNumberGenerator" \ --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": "TanishkB/RandomNumberGenerator", "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 "TanishkB/RandomNumberGenerator" \ --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": "TanishkB/RandomNumberGenerator", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use TanishkB/RandomNumberGenerator with Docker Model Runner:
docker model run hf.co/TanishkB/RandomNumberGenerator
Training in progress, epoch 1
Browse files- README.md +4 -4
- config.json +1 -1
- model.safetensors +1 -1
- runs/Aug18_16-22-25_91af6bbf27c2/events.out.tfevents.1755534172.91af6bbf27c2.423.0 +3 -0
- training_args.bin +2 -2
README.md
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model_name: Philosopher
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tags:
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licence: license
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---
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### Framework versions
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- TRL: 0.21.0
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- Transformers: 4.55.
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- Pytorch: 2.6.0+cu124
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- Tokenizers: 0.21.
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## Citations
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model_name: Philosopher
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tags:
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- generated_from_trainer
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- sft
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- trl
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licence: license
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---
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### Framework versions
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- TRL: 0.21.0
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- Transformers: 4.55.1
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- Pytorch: 2.6.0+cu124
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- Datasets: 4.0.0
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- Tokenizers: 0.21.4
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## Citations
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config.json
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"rope_theta": 1000000.0,
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"sliding_window": 512,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.55.
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"use_bidirectional_attention": false,
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"use_cache": true,
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"vocab_size": 262144
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"rope_theta": 1000000.0,
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"sliding_window": 512,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.55.1",
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"use_bidirectional_attention": false,
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"use_cache": true,
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"vocab_size": 262144
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model.safetensors
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runs/Aug18_16-22-25_91af6bbf27c2/events.out.tfevents.1755534172.91af6bbf27c2.423.0
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training_args.bin
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