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Model: THGLab/Llama-3.1-8B-GeomLlama-xyz
Source: Original Platform

README.md

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+---
+license: llama3.1
+base_model: meta-llama/Llama-3.1-8B-Instruct
+library_name: transformers
+pipeline_tag: text-generation
+language:
+- en
+tags:
+- chemistry
+- molecular-geometry
+- conformer-generation
+- smiles
+- xyz
+- geom
+- llama
+- axolotl
+- arxiv:2607.13350
+datasets:
+- GEOM
+---
+
+# Llama-3.1-8B-GeomLlama-xyz
+
+**Built with Llama. Built with Axolotl.**
+
+GeomLlama-xyz is a fine-tune of **Llama-3.1-8B-Instruct** that generates 3D
+molecular conformer geometries directly from a SMILES string, emitting each
+structure as **Cartesian XYZ coordinates** (one `element x y z` line per atom). It
+is one of two models from our paper; the companion model,
+[Llama-3.1-8B-GeomLlama-zmatrix](https://huggingface.co/THGLab/Llama-3.1-8B-GeomLlama-zmatrix),
+emits Fenske–Hall Z-matrix internal coordinates instead.
+
+The model was trained jointly ("hybrid") on **GEOM-QM9** and **GEOM-Drugs**, so it
+covers both small molecules and larger drug-like molecules with a single set of
+weights.
+
+## Quick start
+
+The model was trained in the Alpaca instruction format. Reproduce the exact
+inference prompt used for the paper's numbers:
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "THGLab/Llama-3.1-8B-GeomLlama-xyz"
+tok = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto")
+
+smiles = "Cc1cccc(CSc2nnnn2-c2ccccc2)c1"
+prompt = (
+    "### Instruction:\n"
+    "You can generate accurate molecular coordinates from a prompt "
+    "containing a SMILES string.\n\n"
+    "### Input:\n"
+    "Generate a realistic equilibrium geometry for the molecule with the "
+    f"following SMILES string in xyz format: {smiles}\n\n"
+    "### Response:\n"
+)
+
+inputs = tok(prompt, return_tensors="pt").to(model.device)
+out = model.generate(**inputs, max_new_tokens=3072, do_sample=True, temperature=1.0, top_p=0.95)
+print(tok.decode(out[0][inputs.input_ids.shape[1]:], skip_special_tokens=True))
+```
+
+Sample many completions per SMILES (each is one candidate conformer) to build a
+conformer ensemble. `T=1.0, top_p=0.95` and `T=1.2, top_p=0.95` are good defaults.
+
+### Output format
+
+One atom per line, `element x y z` in Ångström:
+
+```
+C -4.344237 -2.044144 -0.978303
+C -3.501234  ...
+...
+```
+
+Parse directly as an XYZ block (no header row is emitted).
+
+> View z-matrix or xyz coordinates easily at
+> [doublemolview.streamlit.app](https://doublemolview.streamlit.app).
+
+## Training
+
+- **Base:** meta-llama/Llama-3.1-8B-Instruct
+- **Framework:** [Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
+- **Method:** LoRA (r = 32, α = 16, dropout 0.05, all linear layers), merged into the base weights
+- **Epochs:** 4 · **LR:** 3e-4, cosine · **Optimizer:** adamw_bnb_8bit
+- **Sequence length:** 4096, sample packing · **Precision:** bf16
+- **Data:** GEOM-QM9 + GEOM-Drugs, Cartesian XYZ targets (`ori_xyz`), plus the
+  [Alpaca](https://huggingface.co/datasets/tatsu-lab/alpaca) instruction dataset for
+  general-instruction rehearsal
+
+## Citation
+
+Paper: *How Well Can Frontier Large Language Models Generate Structures? High Quality
+Prediction of Molecular Geometries with Help from Fine-Tuning* —
+[arXiv:2607.13350](https://arxiv.org/abs/2607.13350). Please cite the paper and the
+underlying GEOM dataset (Axelrod & Gómez-Bombarelli, *Scientific Data*, 2022) if you
+use this model.
+
+```bibtex
+@misc{cavanagh2026geomllama,
+  title         = {How Well Can Frontier Large Language Models Generate Structures?
+                   High Quality Prediction of Molecular Geometries with Help from Fine-Tuning},
+  author        = {Cavanagh, Joseph M. and Arnold, Jonathan B. and Alteri, Giovanni Battista
+                   and Gritsevskiy, Andrew and Head-Gordon, Teresa},
+  year          = {2026},
+  eprint        = {2607.13350},
+  archivePrefix = {arXiv},
+  url           = {https://arxiv.org/abs/2607.13350}
+}
+```
+
+## License
+
+Governed by the [Llama 3.1 Community License](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/LICENSE).
+By using this model you agree to its terms. Built with Llama.