Text Generation
Transformers
Safetensors
phi3
torchwright
compiled-transformer
calculator_advanced
text-generation-inference
Instructions to use physicsrob/torchwright-calculator-advanced-max-digits-9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use physicsrob/torchwright-calculator-advanced-max-digits-9 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="physicsrob/torchwright-calculator-advanced-max-digits-9")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("physicsrob/torchwright-calculator-advanced-max-digits-9") model = AutoModelForCausalLM.from_pretrained("physicsrob/torchwright-calculator-advanced-max-digits-9", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use physicsrob/torchwright-calculator-advanced-max-digits-9 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "physicsrob/torchwright-calculator-advanced-max-digits-9" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "physicsrob/torchwright-calculator-advanced-max-digits-9", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/physicsrob/torchwright-calculator-advanced-max-digits-9
- SGLang
How to use physicsrob/torchwright-calculator-advanced-max-digits-9 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 "physicsrob/torchwright-calculator-advanced-max-digits-9" \ --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": "physicsrob/torchwright-calculator-advanced-max-digits-9", "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 "physicsrob/torchwright-calculator-advanced-max-digits-9" \ --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": "physicsrob/torchwright-calculator-advanced-max-digits-9", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use physicsrob/torchwright-calculator-advanced-max-digits-9 with Docker Model Runner:
docker model run hf.co/physicsrob/torchwright-calculator-advanced-max-digits-9
Upload folder using huggingface_hub
Browse files- .gitattributes +1 -0
- README.md +2 -2
- config.json +9 -3
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## Size
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## Size
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The checkpoint stores 75.46 GB of dense fp32 weights (18,864,201,728 entries) at compile width d=8192.
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torchwright_truth.json
ADDED
|
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torchwright_truth_support.npz
ADDED
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version https://git-lfs.github.com/spec/v1
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| 1 |
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{
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| 2 |
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"$schema": "https://json-schema.org/draft/2020-12/schema",
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| 3 |
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"$id": "https://github.com/physicsrob/torchwright/blob/main/torchwright/compiler/torchwright_truth_v1.schema.json",
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| 4 |
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"title": "torchwright compiled artifact truth manifest v1",
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| 5 |
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"type": "object",
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| 6 |
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"required": [
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| 7 |
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"format",
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| 8 |
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"integrity",
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| 9 |
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"artifact",
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| 10 |
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"build",
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| 11 |
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"model",
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| 12 |
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"token_io",
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| 13 |
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"graphs",
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| 14 |
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"schedule",
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| 15 |
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"residual_stream",
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| 16 |
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"physical_layout",
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| 17 |
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"parameter_support",
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| 18 |
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"observability",
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| 19 |
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"runtime_contract",
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| 20 |
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"intervention_contract",
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| 21 |
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"reference_fixtures"
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| 22 |
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],
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| 23 |
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"properties": {
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| 24 |
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"format": {"const": "torchwright.truth.v1"},
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| 25 |
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"$schema": {"type": "string"},
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| 26 |
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"integrity": {
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| 27 |
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"type": "object",
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| 28 |
+
"required": ["sha256", "scope"],
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| 29 |
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"properties": {
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| 30 |
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"sha256": {"type": "string", "pattern": "^[0-9a-f]{64}$"},
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| 31 |
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"scope": {"type": "string"}
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| 32 |
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}
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| 33 |
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},
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| 34 |
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"artifact": {
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| 35 |
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"type": "object",
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| 36 |
+
"required": ["kind", "architecture", "files"],
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| 37 |
+
"properties": {
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| 38 |
+
"kind": {"const": "huggingface_causal_lm_bundle"},
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| 39 |
+
"architecture": {"enum": ["phi3", "custom"]},
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| 40 |
+
"files": {
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| 41 |
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"type": "object",
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| 42 |
+
"additionalProperties": {
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| 43 |
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"type": "object",
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| 44 |
+
"required": ["sha256", "bytes"],
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| 45 |
+
"properties": {
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| 46 |
+
"sha256": {"type": "string", "pattern": "^[0-9a-f]{64}$"},
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| 47 |
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"bytes": {"type": "integer", "minimum": 0}
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| 48 |
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}
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| 49 |
+
}
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| 50 |
+
}
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| 51 |
+
}
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| 52 |
+
},
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| 53 |
+
"build": {"type": "object"},
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| 54 |
+
"model": {"type": "object"},
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| 55 |
+
"token_io": {"type": "object"},
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| 56 |
+
"graphs": {
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| 57 |
+
"type": "object",
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| 58 |
+
"required": ["source", "lowered", "realization_map"],
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| 59 |
+
"properties": {
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| 60 |
+
"source": {"$ref": "#/$defs/graph"},
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| 61 |
+
"lowered": {"$ref": "#/$defs/graph"},
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| 62 |
+
"realization_map": {"type": "array"}
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| 63 |
+
}
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| 64 |
+
},
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| 65 |
+
"schedule": {
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| 66 |
+
"type": "object",
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| 67 |
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"required": ["assignment", "realizations", "layers"]
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| 68 |
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},
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| 69 |
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"residual_stream": {
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| 70 |
+
"type": "object",
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| 71 |
+
"required": ["width", "states"]
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| 72 |
+
},
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| 73 |
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"physical_layout": {
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| 74 |
+
"type": "object",
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| 75 |
+
"required": ["matrices", "placements", "checkpoint_parameter_map"]
|
| 76 |
+
},
|
| 77 |
+
"parameter_support": {
|
| 78 |
+
"type": "object",
|
| 79 |
+
"required": ["file", "format", "tensors"]
|
| 80 |
+
},
|
| 81 |
+
"observability": {"type": "object"},
|
| 82 |
+
"runtime_contract": {"type": "object"},
|
| 83 |
+
"intervention_contract": {"type": "object"},
|
| 84 |
+
"reference_fixtures": {"type": "object"},
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| 85 |
+
"metadata": {"type": "object"}
|
| 86 |
+
},
|
| 87 |
+
"$defs": {
|
| 88 |
+
"graph": {
|
| 89 |
+
"type": "object",
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| 90 |
+
"required": ["root", "nodes", "sha256"],
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| 91 |
+
"properties": {
|
| 92 |
+
"root": {"type": "string"},
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| 93 |
+
"nodes": {
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| 94 |
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"type": "array",
|
| 95 |
+
"items": {
|
| 96 |
+
"type": "object",
|
| 97 |
+
"required": ["id", "op", "width", "inputs", "value_contract"],
|
| 98 |
+
"properties": {
|
| 99 |
+
"region": {"type": ["string", "null"]}
|
| 100 |
+
}
|
| 101 |
+
}
|
| 102 |
+
},
|
| 103 |
+
"semantic_regions": {
|
| 104 |
+
"type": "array",
|
| 105 |
+
"items": {
|
| 106 |
+
"type": "object",
|
| 107 |
+
"required": ["id", "op", "operands", "results"],
|
| 108 |
+
"properties": {
|
| 109 |
+
"id": {"type": "string"},
|
| 110 |
+
"op": {"type": "string"},
|
| 111 |
+
"parent": {"type": ["string", "null"]},
|
| 112 |
+
"params": {"type": "object"},
|
| 113 |
+
"operands": {"type": "array", "items": {"type": "string"}},
|
| 114 |
+
"results": {"type": "array", "items": {"type": "string"}},
|
| 115 |
+
"annotation": {"type": ["string", "null"]}
|
| 116 |
+
}
|
| 117 |
+
}
|
| 118 |
+
},
|
| 119 |
+
"sha256": {"type": "string", "pattern": "^[0-9a-f]{64}$"}
|
| 120 |
+
}
|
| 121 |
+
}
|
| 122 |
+
}
|
| 123 |
+
}
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