Text Generation
Transformers
PyTorch
Safetensors
English
llama
text-generation-inference
unsloth
trl
sft
Instructions to use Manirajan/interview_tiny1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Manirajan/interview_tiny1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Manirajan/interview_tiny1")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Manirajan/interview_tiny1") model = AutoModelForCausalLM.from_pretrained("Manirajan/interview_tiny1") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Manirajan/interview_tiny1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Manirajan/interview_tiny1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Manirajan/interview_tiny1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Manirajan/interview_tiny1
- SGLang
How to use Manirajan/interview_tiny1 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 "Manirajan/interview_tiny1" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Manirajan/interview_tiny1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "Manirajan/interview_tiny1" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Manirajan/interview_tiny1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Unsloth Studio new
How to use Manirajan/interview_tiny1 with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Manirajan/interview_tiny1 to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Manirajan/interview_tiny1 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Manirajan/interview_tiny1 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Manirajan/interview_tiny1", max_seq_length=2048, ) - Docker Model Runner
How to use Manirajan/interview_tiny1 with Docker Model Runner:
docker model run hf.co/Manirajan/interview_tiny1
Trained with Unsloth
Browse files- README.md +1 -0
- config.json +31 -0
- generation_config.json +7 -0
- pytorch_model.bin +3 -0
README.md
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- unsloth
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- llama
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- trl
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base_model: unsloth/tinyllama
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---
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- unsloth
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- llama
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- trl
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- sft
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base_model: unsloth/tinyllama
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---
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config.json
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{
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"_name_or_path": "unsloth/tinyllama",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 2048,
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"initializer_range": 0.02,
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"intermediate_size": 5632,
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"max_position_embeddings": 2048,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 22,
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"num_key_value_heads": 4,
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"pad_token_id": 0,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 10000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.41.2",
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"unsloth_version": "2024.6",
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"use_cache": true,
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"vocab_size": 32000
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}
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generation_config.json
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{
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"bos_token_id": 1,
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"eos_token_id": 2,
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"max_length": 2048,
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"pad_token_id": 0,
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"transformers_version": "4.41.2"
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:d938d7e59bb75d03da1e21584d99a3adf86d086158345abd2c1b1716ae0c0006
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size 2200164718
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