Instructions to use mygitphase/guhan-30b-fp8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mygitphase/guhan-30b-fp8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="mygitphase/guhan-30b-fp8", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("mygitphase/guhan-30b-fp8", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use mygitphase/guhan-30b-fp8 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "mygitphase/guhan-30b-fp8" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mygitphase/guhan-30b-fp8", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/mygitphase/guhan-30b-fp8
- SGLang
How to use mygitphase/guhan-30b-fp8 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 "mygitphase/guhan-30b-fp8" \ --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": "mygitphase/guhan-30b-fp8", "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 "mygitphase/guhan-30b-fp8" \ --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": "mygitphase/guhan-30b-fp8", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use mygitphase/guhan-30b-fp8 with Docker Model Runner:
docker model run hf.co/mygitphase/guhan-30b-fp8
| { | |
| "architectures": [ | |
| "SarvamMoEForCausalLM" | |
| ], | |
| "attention_dropout": 0.0, | |
| "attn_implementation": null, | |
| "auto_map": { | |
| "AutoConfig": "configuration_sarvam_moe.SarvamMoEConfig", | |
| "AutoModel": "modeling_sarvam_moe.SarvamMoEModel", | |
| "AutoModelForCausalLM": "modeling_sarvam_moe.SarvamMoEForCausalLM" | |
| }, | |
| "dtype": "float32", | |
| "embedding_dropout": 0.0, | |
| "eos_token_id": 1, | |
| "first_k_dense_replace": 1, | |
| "head_dim": 64, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "initializer_range": 0.006, | |
| "intermediate_size": 8192, | |
| "max_position_embeddings": 131072, | |
| "max_window_layers": 19, | |
| "model_type": "sarvam_moe", | |
| "moe_intermediate_size": 1024, | |
| "moe_router_enable_expert_bias": true, | |
| "moe_shared_expert_intermediate_size": 1024, | |
| "n_group": 1, | |
| "norm_topk_prob": true, | |
| "num_attention_heads": 64, | |
| "num_experts": 128, | |
| "num_experts_per_tok": 6, | |
| "num_hidden_layers": 19, | |
| "num_key_value_heads": 4, | |
| "num_shared_experts": 1, | |
| "output_dropout": 0.0, | |
| "output_router_logits": false, | |
| "pad_token_id": 0, | |
| "rms_norm_eps": 1e-06, | |
| "rope_scaling": null, | |
| "rope_theta": 8000000, | |
| "routed_scaling_factor": 2.5, | |
| "router_dtype": "fp32", | |
| "score_function": "sigmoid", | |
| "tie_word_embeddings": false, | |
| "topk_group": 1, | |
| "transformers_version": "4.57.1", | |
| "use_bias": false, | |
| "use_cache": true, | |
| "use_qk_norm": true, | |
| "use_qkv_bias": false, | |
| "use_rmsnorm": true, | |
| "vocab_size": 262144, | |
| "quantization_config": { | |
| "config_groups": { | |
| "group_0": { | |
| "input_activations": { | |
| "dynamic": false, | |
| "num_bits": 8, | |
| "type": "float" | |
| }, | |
| "weights": { | |
| "dynamic": false, | |
| "num_bits": 8, | |
| "type": "float" | |
| }, | |
| "targets": [ | |
| "Linear" | |
| ] | |
| } | |
| }, | |
| "ignore": [ | |
| "lm_head" | |
| ], | |
| "quant_algo": "FP8", | |
| "kv_cache_scheme": { | |
| "dynamic": false, | |
| "num_bits": 8, | |
| "type": "float" | |
| }, | |
| "producer": { | |
| "name": "modelopt", | |
| "version": "0.42.0rc1.dev9+ge53ca61b7.d20260326" | |
| }, | |
| "quant_method": "modelopt" | |
| } | |
| } |