Text Generation
Transformers
Safetensors
phi3
Generated from Trainer
sft
hf_jobs
trl
conversational
custom_code
text-generation-inference
Instructions to use misterJB/arkadas-field-717hz with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use misterJB/arkadas-field-717hz with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="misterJB/arkadas-field-717hz", trust_remote_code=True) 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("misterJB/arkadas-field-717hz", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("misterJB/arkadas-field-717hz", trust_remote_code=True, 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 misterJB/arkadas-field-717hz with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "misterJB/arkadas-field-717hz" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "misterJB/arkadas-field-717hz", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/misterJB/arkadas-field-717hz
- SGLang
How to use misterJB/arkadas-field-717hz 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 "misterJB/arkadas-field-717hz" \ --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": "misterJB/arkadas-field-717hz", "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 "misterJB/arkadas-field-717hz" \ --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": "misterJB/arkadas-field-717hz", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use misterJB/arkadas-field-717hz with Docker Model Runner:
docker model run hf.co/misterJB/arkadas-field-717hz
ARKADAS 717Hz b37 identity-repair b34-36 corpus 6500steps
Browse files- README.md +4 -4
- config.json +1 -1
- generation_config.json +1 -1
- model.safetensors +1 -1
- tokenizer_config.json +1 -0
- training_args.bin +2 -2
README.md
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model_name: arkadas-field-717hz
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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: 1.
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- Transformers: 5.
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- Pytorch: 2.8.0
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- Datasets:
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- Tokenizers: 0.22.2
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## Citations
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model_name: arkadas-field-717hz
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tags:
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- generated_from_trainer
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- trl
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- hf_jobs
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- sft
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licence: license
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---
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### Framework versions
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- TRL: 1.7.1
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- Transformers: 5.13.0
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- Pytorch: 2.8.0
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- Datasets: 5.0.0
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- Tokenizers: 0.22.2
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## Citations
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config.json
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},
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"sliding_window": 2047,
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"tie_word_embeddings": false,
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"transformers_version": "5.
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"use_cache": false,
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"vocab_size": 32064
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}
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},
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"sliding_window": 2047,
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"tie_word_embeddings": false,
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"transformers_version": "5.13.0",
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"use_cache": false,
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"vocab_size": 32064
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}
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generation_config.json
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}
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model.safetensors
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tokenizer_config.json
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"eos_token": "<|endoftext|>",
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"is_local": false,
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"model_max_length": 4096,
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training_args.bin
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