Instructions to use thashim/test_model4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thashim/test_model4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="thashim/test_model4")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("thashim/test_model4") model = AutoModelForCausalLM.from_pretrained("thashim/test_model4") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use thashim/test_model4 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "thashim/test_model4" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "thashim/test_model4", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/thashim/test_model4
- SGLang
How to use thashim/test_model4 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 "thashim/test_model4" \ --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": "thashim/test_model4", "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 "thashim/test_model4" \ --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": "thashim/test_model4", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use thashim/test_model4 with Docker Model Runner:
docker model run hf.co/thashim/test_model4
Training in progress, epoch 1
Browse files
config.json
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{
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"_name_or_path": "EleutherAI/pythia-160m",
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"architectures": [
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"GPTNeoXForCausalLM"
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],
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"attention_bias": true,
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"attention_dropout": 0.0,
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"bos_token_id": 0,
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"classifier_dropout": 0.1,
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"eos_token_id": 0,
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"hidden_act": "gelu",
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"hidden_dropout": 0.0,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 2048,
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"model_type": "gpt_neox",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"rope_scaling": null,
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"rotary_emb_base": 10000,
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"rotary_pct": 0.25,
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"tie_word_embeddings": false,
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"torch_dtype": "float32",
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"transformers_version": "4.41.2",
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"use_cache": true,
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"use_parallel_residual": true,
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"vocab_size": 50304
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}
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logs/events.out.tfevents.1717615820.sphinx8.stanford.edu
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logs/events.out.tfevents.1717615910.sphinx8.stanford.edu
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model.safetensors
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training_args.bin
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